Consequences of Obesity on Women’s Health


Department of Obstetrics & Gynecology
University of Utah

Obesity among women of reproductive age is a major health threat in the United States and contributes to the overall morbidity, mortality and costs associated with overweight and obesity. In the year 2000, 117 billion dollars in health care costs and 300,000 deaths were attributed to obesity (Allison, Fontaine, Manson, Stevens, & VanItallie, 1999; Centers for Disease Control and Prevention). Body mass index (BMI), the most commonly used measure to define obesity, is calculated by dividing a woman’s weight in kilograms by her height in meters squared. The International Obesity Task Force defined overweight and obesity using the following classification of body mass index (BMI, defined as kg/m2): <19 underweight, 19-24.9 normal weight, 25-29.9 overweight, 30- 34.9 class I obesity, 35-39.9 class II obesity, and >40 class III obesity. (International Obesity Task Force, 1998) Using this classification system, over 127 million American adults are overweight (BMI>25), 60 million are obese (BMI>30), and 9 million are severely obese (BMI>40) (American Obesity Association).

For the first time in over twenty years the number of obese women nationwide did not increase; however the majority of adult American women are still overweight or obese (Ogden et al., 2006). In 2003-2004, 62% of women were overweight or obese, 33% were obese, and 7% were severely obese (Ogden et al., 2006). This is significantly higher than the NHANES data from 1988-94, where the rates were 50%, 26%, and 4.0 % respectively (Flegal, Carroll, Kuczmarski, & Johnson, 1998; Flegal, Carroll, Ogden, & Johnson, 2002).

Overweight and obesity have long been known to increase the risk and severity of many chronic diseases including type 2 diabetes mellitus, cardiovascular disease, hypertension and arthritis (Field et al., 2001). Table 1 provides a list of the major morbidities associated with obesity. While this list of health consequence associated with obesity is extensive, the most dire consequence, mortality, is also increased. The Nurses’ Health Study prospectively studied over 116,000 women who were disease free at enrollment for 24 years. All cause and disease specific mortality increased in this population with increasing BMI, even after controlling for age, smoking, family history, menopausal status, activity and alcohol consumption (Hu et al., 2004).

Obese women, when compared to lean women, are more likely to suffer from endometrial cancer, breast cancer, stress urinary incontinence, gall bladder disease and depression (American Obesity Association, 2002). Also, they are less likely to participate in health care maintenance activities, such as mammograms and gynecologic exams, which may delay the identification of disease and may worsen prognosis (Fontaine, Heo, & Allison, 2001).

Table 1 Morbidities Associated with Obesity

Type II Diabetes Renal Cancer
Cardiovascular Disease Gallbladder Disease
Hypertension Stress Urinary Incontinence
Hyperlipidemia Menstrual Irregularities
Arthritis Carpal Tunnel Syndrome
Postmenopausal Breast Cancer Sleep Apnea
Endometrial Cancer Asthma
Gastrointestinal Cancer Depression and poor QOL

There has been little attention paid to the complications of obesity in women of reproductive age. While obesity complications of pregnancy have been studied, significantly less attention has been paid to postpartum and longterm complications in these women. (The paucity of research during the puerperium is not limited to obese women.) National studies which identify trends in body mass indices, including the National Health and Nutrition Examination Survey (NHANES) and the Behavioral Risk Factor Surveillance System specifically exclude pregnant women from their analyses (Flegal et al., 2002; Freedman, Khan, Serdula, Galuska, & Dietz, 2002). Several studies have shown that obese pregnant women are at increased risk for adverse pregnancy outcomes including gestational diabetes, pre-eclampsia, macrosomia, fetal anomalies, intrauterine fetal demise, early neonatal death, induction, cesarean delivery, postpartum hemorrhage, and infection (Cnattingius, Bergstrom, Lipworth, & Kramer, 1998; Ehrenberg, Dierker, Milluzzi, & Mercer, 2002; Jensen et al., 2003; Lu et al., 2001; Sebire et al., 2001; Watkins, Rasmussen, Honein, Botto, & Moore, 2003).

To explore the impact of overweight and obesity during pregnancy in Utah, birth certificate data from 1991 to 2001 were analyzed. Maternal obesity, as defined by the proportion of women with a BMI greater than 30 at delivery has increased nearly 40% over this past decade in Utah (D.Y. LaCoursiere, Bloebaum, Duncan, & Varner, 2004). (See figure 1). A similar increase in the percent of women who were overweight (BMI >25) or obese (BMI >30) prior to pregnancy has also been identified (D.Y. LaCoursiere et al., 2004). In 2001, 40.2% of women were overweight or obese before delivery. The attributable fraction of cesarean delivery in the overweight and obese was 0.388 (95% CI: 0.369 – 0.407) (D. Y. LaCoursiere, Bloebaum, Duncan, & Varner, 2005). This means that after controlling for other factors, nearly 40% of cesarean deliveries in the overweight and obese are due to increased maternal weight. Statewide, among all women having a cesarean in 2001, 1 in 7 is attributable to overweight and obesity. Cesarean delivery rates are shown in figure 2 for women with and without risk factors of diabetes and hypertension. Increases in preeclampsia have also been seen with the rise in maternal overweight and obesity over this same decade (see figure 3). While much of the above information reflects poor outcomes associated with a woman’s weight before pregnancy, excess maternal weight gain during pregnancy also increases the risk of adverse outcomes. The chance of Cesarean delivery, preeclampsia and birth weight over 4000 grams all increase with excessive maternal weight gain in pregnancy. 22 In fact, 40% of women who gain over 35 lbs during their pregnancy are delivered by primary Cesarean delivery (see figure 4).

Utah data have also been used to investigate the association between obesity and postpartum depressive symptoms. To do so we explored the Pregnancy Risk Assessment Monitoring System (PRAMS), a project sponsored by the Centers for Disease Control and Prevention (CDC). PRAMS is a population-based survey of maternal attitudes and experience from preconception through the postpartum period. (Centers for Disease Control and Prevention). The Utah Department of Health (UDOH) participates in this project. One of the questions pertains to the woman’s postpartum mood. She is asked “In the months after your delivery, would you say that you were- Not depressed at all, A little depressed, Moderately depressed, Very Depressed, Very depressed and had to get help?” The response to this question and questions pertaining to stressors were stratified by prepregnancy body mass index. There were 3,439 women included in the analysis. Among overweight and obese women, there was a trend toward more partner associated stress (p=0.057) and they were more likely to report emotional (p<0.001) and traumatic stress (p<0.001). When stratified by BMI categories, the prevalence of moderate or greater depressive symptoms increases at the extremes of BMI (figure 4). After controlling for marital status and income, prepregnancy obesity (BMI≥30) was associated with greater than moderate postpartum depressive symptoms (adjusted odds ratio 1.53 [95% CI:1.15 – 2.02]) (D. Y. Lacoursiere, Baksh, Bloebaum, & Varner, 2006). While limited in its evaluation of depressive symptoms, this database supports the possibility that obese women could be at greater risk for maternal stressors and postpartum depression. Currently a larger prospective study, funded by the National Institutes of Health, is being conducted in our state.

There have been recent studies presenting interesting information on obesity and breast feeding (Oddy et al., 2006) (Li et al., 2005). Increased prepregnancy BMI is associated with shorter breastfeeding duration (Oddy et al., 2006). Maternal obesity and short duration of breast feeding are additive risk factors for childhood overweight (Li et al., 2005). Recently, biologic data support this epidemiologic association between obesity and short duration of breastfeeding. Increased prepregnancy BMI predicts a lower prolactin response to suckling at 48 hours. Prolactin is responsible for stimulating milk production and thus a decrease in responsiveness could lead to a diminished ability to make milk and perhaps contribute to breastfeeding discontinuation (Rasmussen & Kjolhede, 2004). These studies lead to the possibility that an intervention to improve prepregnancy BMI and or maternal weight gain might improve a woman’s ability to breastfeed.

Overweight and obesity significantly impact women’s health. It affects two-thirds of all women nationwide. . Rates of overweight and obesity during pregnancy are increasing in Utah. Data from our state suggest that it is likewise influencing women’s reproductive health outcomes. Overweight and obese Utah women are more likely to have gestational diabetes, preeclampsia, Cesarean delivery postpartum depression and large babies. Information also supports that overweight and obese women have more difficulty continuing to breastfeed. Maternal weight during pregnancy not only effects the woman’s outcome, but also that of her child. While information is needed to prevent the untoward effects of increased BMI in women, even more data are necessary on primary prevention of obesity.


  • Allison, D. B., Fontaine, K. R., Manson, J. E., Stevens, J., & VanItallie, T. B. (1999). Annual deaths attributable to obesity in the United States. Jama, 282(16), 1530-1538.
  • American Obesity Association. AOA fact sheets. from
  • American Obesity Association. (2002). Obesity In The U.S. AOA fact sheets. from
  • Centers For Disease Control and Prevention. Reproductive Health Information Sources, surveillance and research, pregnancy risk assessment monitoring system.
  • Centers for Disease Control and Prevention. Preventing chronic diseases: investing wisely in health. Preventing obesity and chronic diseases through good nutrition and physical activity.
  • Cnattingius, S., Bergstrom, R., Lipworth, L., & Kramer, M. S. (1998). Prepregnancy weight and the risk of adverse pregnancy outcomes.
    N Engl J Med, 338(3), 147-152.
  • Ehrenberg, H. M., Dierker, L., Milluzzi, C., & Mercer, B. M. (2002). Prevalence of maternal obesity in an urban center. Am J Obstet Gynecol, 187(5), 1189-1193.
  • Field, A. E., Coakley, E. H., Must, A., Spadano, J. L., Laird, N., Dietz, W. H., et al. (2001). Impact of overweight on the risk of developing common chronic diseases during a 10-year period. Arch Intern Med, 161(13), 1581-1586.
  • Flegal, K. M., Carroll, M. D., Kuczmarski, R. J., & Johnson, C. L. (1998). Overweight and obesity in the United States: prevalence and trends, 1960-1994. Int J Obes Relat Metab Disord, 22(1), 39-47.
  • Flegal, K. M., Carroll, M. D., Ogden, C. L., & Johnson, C. L. (2002). Prevalence and trends in obesity among U.S. adults, 1999-2000. Jama, 288(14), 1723-1727.
  • Fontaine, K. R., Heo, M., & Allison, D. B. (2001). Body weight and cancer screening among women. J Womens Health Gend Based Med, 10(5), 463-470.
  • Freedman, D. S., Khan, L. K., Serdula, M. K., Galuska, D. A., & Dietz, W. H. (2002). Trends and correlates of class 3 obesity in the United States from 1990 through 2000. Jama, 288(14), 1758-1761.
  • Hu, F. B., Willett, W. C., Li, T., Stampfer, M. J., Colditz, G. A., & Manson, J. E. (2004). Adiposity as compared with physical activity in predicting mortality among women. N Engl J Med, 351(26), 2694-2703.
  • International Obesity Task Force. (1998). Managing the global epidemic of obesity. Report of the WHO consultation on obesity, World Health Organization. Geneva.
  • Jensen, D. M., Damm, P., Sorensen, B., Molsted-Pedersen, L., Westergaard, J. G., Ovesen, P., et al. (2003). Pregnancy outcome and prepregnancy body mass index in 2459 glucose-tolerant Danish women. Am J Obstet Gynecol, 189(1), 239-244.
  • Lacoursiere, D. Y., Baksh, L., Bloebaum, L., & Varner, M. W. (2006). Maternal body mass index and self-reported postpartum depressive symptoms. Matern Child Health J, 10(4), 385-390.
  • LaCoursiere, D. Y., Bloebaum, L., Duncan, J. D., & Varner, M. V. (2004). Population-based trends in maternal obesity, Utah 1991-2001. J Soc Gynecol Investig, 11(2 Supplement), 191a.
  • LaCoursiere, D. Y., Bloebaum, L., Duncan, J. D., & Varner, M. W. (2005). Population-based trends and correlates of maternal overweight and obesity, Utah 1991-2001. Am J Obstet Gynecol, 192(3), 832-839.
  • Li, C., Kaur, H., Choi, W. S., Huang, T. T., Lee, R. E., & Ahluwalia, J. S. (2005). Additive interactions of maternal prepregnancy BMI and breast-feeding on childhood overweight. Obes Res, 13(2), 362-371.
  • Lu, G. C., Rouse, D. J., DuBard, M., Cliver, S., Kimberlin, D., & Hauth, J. C. (2001). The effect of the increasing prevalence of maternal
    obesity on perinatal morbidity. Am J Obstet Gynecol, 185(4), 845-849.
  • Oddy, W. H., Li, J., Landsborough, L., Kendall, G. E., Henderson, S., & Downie, J. (2006). The association of maternal overweight and obesity with breastfeeding duration. J Pediatr, 149(2), 185-191.
  • Ogden, C. L., Carroll, M. D., Curtin, L. R., McDowell, M. A., Tabak, C. J., & Flegal, K. M. (2006). Prevalence of overweight and obesity in the United States, 1999-2004. Jama, 295(13), 1549-1555.
  • Rasmussen, K. M., & Kjolhede, C. L. (2004). Prepregnant overweight and obesity diminish the prolactin response to suckling in the first week postpartum. Pediatrics, 113(5), e465-471.
  • Sebire, N. J., Jolly, M., Harris, J. P., Wadsworth, J., Joffe, M., Beard, R. W., et al. (2001). Maternal obesity and pregnancy outcome: a study of 287,213 pregnancies in London. Int J Obes Relat Metab Disord, 25(8), 1175-1182.
  • Watkins, M. L., Rasmussen, S. A., Honein, M. A., Botto, L. D., & Moore, C. A. (2003). Maternal obesity and risk for birth defects. Pediatrics, 111(5 Part 2), 1152-1158.

Headache and Sexual Abuse in Women in a Headache Clinic in Utah


Headache is a common disorder in women and chronic daily headache is also more common in women. Childhood sexual abuse has been found to be frequent among women who have disabling headache. We wished to determine the frequency of sexual abuse as well as other forms of abuse in a headache clinic in Utah. Methods: Patients filled out a questionnaire using a personal digital assistant (PDA). Patients also completed depression and somatic symptom severity measures. Results: Two-hundred twenty-two women completed the study. The majority of the women had migraine, over half had chronic daily headache. Sexual abuse in childhood was reported in 34% of women; physical abuse was reported in 32% of women, and emotional abuse in 26%. Of those reporting sexual abuse, 41% of women reported occurrences before they were 12 years and 82% reported occurrences as adolescents less than 20 years. Risk for abuse did not follow socio-economic level, number of headaches, but was more prevalent in women with a lower level of education. Depression was common in over one-half of the patients and women who were abused had an increase in depressive indicators. Multiple somatic symptoms were more common in abused women. Migraine headaches occurred in 85.6% of the patients; 43.7% had daily migraine headaches. Some form of violence was experienced by 63.1% of the women. Conclusion: A reported history of abuse is common among women seen in a headache clinic. Clues to identifying women who have been abused are present when there are increased somatic symptoms and depression. Practitioners should be aware that abuse is common and address this with women with headache.


Headache is a common disorder in women. In fact, almost twenty percent of all women in the population suffer from migraine (Lipton, Stewart, Diamond, Diamond & Reed, 2001). About 4% of the adult population suffers from some sort of chronic daily headache; however, women again share the burden of daily headache twice as often as men (Scher, Stewart, Liberman & Lipton, 1998; Stewart & Lipton, 1993; Silberstein and Lipton, 2000). Sexual abuse in childhood has been estimated to occur in 15-25% of women (Leserman, 2005; Howard, 1995). These women are found to have more chronic complaints (pelvic pain, irritable bowel syndrome), use more health care resources (Walker et al., 1999b; Hilden 2004), have more physical symptoms and have an increase in life-time health problems (Leserman, 2005; Walker et al., 1999a; Roberts, 1996). There is evidence to suggest that a history of childhood sexual abuse may also increase the severity of headache as well as lead to increase in other pain and depression (Felitti, 1991; Domino & Haber, 1997; Emiroglu, Kurul, Akay, Miral & Dirik, 2004). We sought to find the frequency of sexual abuse among women visiting a headache specialty clinic in Utah.


The study was approved by the IRB. All participants were women seen for evaluation and treatment of headache in the University of Utah Headache Clinic. All participants were examined and diagnosed by specialists in headache (KBD, SB). Women patients who met the following criteria were invited to participate: 1) primary headache disorder defined by the International Classification of Headache Disorders (2004) 2) women over 18 years of age; 3) willingness and ability to perform a self-administered questionnaire on a Personal Digital Assistant (PDA). Women were excluded from the study if they were not able to complete the questionnaire on the PDA or if they were unable to read English.

The patient’s diagnosis and the average number of headache days per month over the previous three months were entered by the headache specialist. The electronic questionnaire was designed with Pendragon® Forms 3.2 computer software (Pendragon Software Corporation, Libertyville, IL). Patients responded to questions on the following topics: age, race, household income, highest educational level attained, age of onset of headaches, impact of headaches on daily life, severity of current depression, and somatic symptoms. The questionnaire collected information on physical abuse, sexual abuse, and ‘fear for life’ (emotional abuse) in time periods: childhood years (12 years old), teenage years (13 to 20 years old), adulthood (≥21 years old) and current (within the past year). The participants were asked if they had been the recipient of other abusive behaviors such as: threats, aggression, intimidation, isolation, and coercion. They were also asked if they had stress due to fear of threats or felt they were at risk for future abuse. The participants were asked whether they had witnessed 1) abusive behavior between adults, and 2) drug/alcohol abuse by adults in their childhood home.

The questionnaire also included a disability scale, the Headache Impact Test (HIT-6) (Kosinski et al., 2003) that produces a score ranging from 36 to 78. In this test, there are four levels of disability based on the HIT-6 scores: ‘little or no impact’ for scores less than 49, ‘some impact’ for scores 50-55, ‘substantial impact’ for scores 56-59, ‘very severe impact’ for scores more than 60.

Determination of current (over the prior two weeks) depression was performed using the Personal Health Questionnaire 9 (PHQ-9) (Kroenke, Spitzer & Williams, 2001), that produces a score ranging from 0 to 27. Five levels of depression severity exist based on the PHQ-9 scores: ‘minimal’ for scores 0-4, ‘mild’ for scores 5-9, ‘moderate’ for scores 10-14, ‘moderately severe’ for scores 15-19, and ‘severe’ for scores 20 and above.

The type and severity of current somatic symptoms (over the prior 4 weeks) was assessed using Personal Health Questionnaire 15 (PHQ-15) (Kroenke, Spitzer & Williams, 2002). The symptoms include: joint or limb pain, dizziness, headaches, back pain, abdominal pain, chest pain, breathing trouble, fainting, gas or indigestion, sleeping trouble, palpitations, menstrual problems, diarrhea (constipation), and sexual pain/problems. In this test, 15 symptoms were graded by the patient as ‘not bothered at all’ (scored as 0), ‘bothered a little’ (scored as 1), or ‘bothered a lot’ (scored as 2). The PHQ-15 reveals four levels of somatic symptom severity: ‘minimal’ for 0-4, ‘low’ for 5-9, ‘medium’ for 10-14, and ‘high’ for 15-30.

Table 1. Demographics of Headache Clinic Population Compared to the State of Utah Population
Table 1. Demographics of Headache Clinic Population Compared to the State of Utah Population

Patients took about 15 minutes to answer the questions. A security code was entered at the end of the survey, uploaded data to a central database using the PDA, and synchronized to a central database through a Pendragen SyncServe computer software. The database was kept at the University of Toledo, Ohio which was the primary site for the study.

Data for Utah were transferred to SPSS for analysis. Chi-square test, t-test, and regression were used for analysis. This study was part of a multi-centered study. Only the data from Utah are presented here. Previous publications of the aggregate data include Tietjen et al. (2007).


There were 222 women who participated in this study. The ages were 18-72 with a mean age of 40.8. The majority of the women were Caucasian. The vast majority, 97%, had attained high school graduation and many, 44%, had attained a baccalaureate degree or higher. Sixty percent of the women had household incomes more than $50,000 and only 10% had incomes less than $20,000. The number of people in a household ranged from 1-12; the average household size was 3.2. See Table 1 for demographic data and its comparison to the demographic

Figure 1. Headache Severity and Disability (HIT-6)
Figure 1. Headache Severity and Disability (HIT-6)

information of women from the State of Utah. The headache clinic population and the female Utah population were found not to significantly differ on race and average number of household members. But the cohort did differ on age (t=16.351, p<0.001), education (Ȥ2=8.309, p<0.01), and income (Ȥ2=66.611, p<0.001). It was found that, on average, the headache clinic sample was significantly older, more educated, and had higher income levels than the female Utah population. Some statistics representing only women were unavailable. For these demographic variables (i.e. income and average household number), information from the general Utah population was used for comparison.

The primary headache type was most frequently migraine (190/222, 85.6%), and less frequently: tension-type (5/222, 2.3%), post-traumatic (12/222, 5.4%), and other (15/222, 6.6%). Headaches occurred less than 15 days per month in 101/222 (45.5%) patients and more than 15 days per month in 121/222 (54.5%) patients. Severe headaches were found in 170/222 (76.6%) patients as defined by the HIT-6 test score of over 60. The average HIT-6 score was 63 and the range of scores was 48-76. See figure 1.

The women reported their headaches to begin between the ages of 1 and 61 years with a mean of 21.5 years. Headaches beginning before the age of 20 were experienced by 105 (47.3%) women.

Moderate to severe depression, as determined by the PHQ-9 score of 15 or greater, occurred in 84 (37.8%) women. Minimal or no depression, indicated by a PHQ-9 score of 0-4, occurred in 76 (34.2%) women. See figure 2.

Figure 2. Depression Severity (PHQ-9)
Figure 2. Depression Severity (PHQ-9)

Somatic symptoms were highly prevalent in this group; 161 (72.5%) women had somatic symptoms that the PHQ-15 determined were of medium or high severity. See figure 3.

Thirty-four (15.3%) women currently or in the past abused drugs or alcohol; 13/34 (38.2%) of these women recalled alcohol or drug abuse to be present in their childhood homes. Some type of violent behavior was reported by 140 (63.1%) women—this includes physical, sexual, and emotional abuse, other abusive behaviors, or had witnessed violent behaviors. Fifty-four (54.3%) of these women reported a personal previous history of sexual abuse (76/140).

Figure 3. Somatic Symptoms (PHQ-15)
Figure 3. Somatic Symptoms (PHQ-15)

Physical abuse (as defined as being hit, punched, slapped, kicked, bitten, grabbed choked, by a family member, current or former spouse, or significant other) occurred in 71 (32%) women. These 71 women indicated that they had been physically abused at different ages, so there was a total of 106 reports of abuse. The physical abuse occurred at 12 years of age or younger (29.2%), 13-20 years of age (38.7%), 21 years of age or older (13.5%). Only 3.8% reported current physical abuse. See figure 4.

Sexual abuse was reported to occur in 76 (34.2%) of women. These 76 women indicated that they had been sexually abused at different ages, so there was a total of 107 reports of abuse. The sexual abuse occurred at 12 years of age or younger (41.1%), 13-20 years of age (39.3%), 21 years of age or older (15.9%); rarely was there current sexual abuse (1.9%). See figure 4.

Emotional Abuse/Fear for life (as defined by being hurt or frightened so badly by a family member that they feared for their life) occurred in 57 (25.7%) women. These 57 women indicated that they had been emotionally abused at different ages, so there was a total of 73 reports of abuse. The emotional abuse occurred at 12 years of age or younger (21.9%), 13-20 years of age (34.2%), 21 years of age or older (38.4%); current emotional abuse occurred in 5.5% of the 57 women. See figure 4.

Figure 4. Age at which Abuse Occurred
Figure 4. Age at which Abuse Occurred

One hundred and one (45.5%) women reported no sexual, physical or emotional abuse.
While patients with a history of physical or sexual abuse showed no statistical increase in headache frequency when compared to patients with no history of physical abuse and sexual abuse, patients with a history of emotional abuse showed an increase in headache frequency when compared to patients with no history of emotional abuse (Ȥ2=13.553, p<0.001).

Women with a history of physical, sexual, or emotional abuse usually reported more than one type of abuse. Of the women who had physical, sexual, and/or emotional abuse 55/121 (45.5%) had witnessed abusive behavior between adults in their childhood home, whereas 18/10 (18.0%) who had never had abuse, had witnessed abusive behavior in their childhood home. See figure 5.

Figure 5. Reports of more than one kind of abuse in a Headache Clinic Population
Figure 5. Reports of more than one kind of abuse in a Headache Clinic Population

Other abusive behaviors (independent of physical, sexual, or emotional abuse) were reported by 107 women. In response to questions about these other abusive behaviors, women reported they had been: threatened (51; 45.5%), shown aggression (44; 19.8%); harassed (42; 18.9%); intimidated (71; 31.98%), isolated (53; 23.9%), and controlled/coerced (52; 23.4%).

Table 2 compares the samples of women with no history of physical, sexual, or emotional abuse (N=101) and the sample of women with a history of physical, sexual, and/or emotional abuse (N=121). The two groups did not differ significantly in age, race, income, number of household members, and headache frequency. The sub-sample of women with a history of physical, sexual and/or emotional abuse had significantly different education levels when compared to those who did not experience any abuse (Ȥ2=10.732, p=0.013).

Table 3 shows the results of linear regression models to fit the somatic symptom severity score (PHQ-15), the depression score (PHQ-9), and the headache-related disability score (HIT-6).
The PHQ-15 score (somatic symptoms) is significantly associated to sexual abuse, emotional abuse, income level and headache frequency. Higher PHQ-15 scores are observed for participants who have had a history of sexual and/or emotional abuse and also for those who experience more than 15 headaches a month. The PHQ-15 score seems to be negatively related to income level (i.e., higher income level relates to lower PHQ-15 score) after controlling for all other factors.
The PHQ-9 score (depression) is significantly associated to emotional abuse, income level, and headache frequency. The presence of emotional abuse, increasing income levels, and increasing headache frequency result in higher PHQ-9 scores; this is quantified by the parameter estimates shown in Table 4. Although sexual abuse was not found to be significantly associated with PHQ-9 at the 0.05 level (p=0.056), it was very close to the significance value and we have chosen to leave this factor in. Again, as with the PHQ-15, the PHQ-9 is negatively associated with income level.
The HIT-6 score was found to be significantly associated only with age and headache frequency. Age was negatively related to the HIT-6 score (i.e., older women show lower HIT-6 scores). The headache frequency seemed to be the major predictor of the HIT-6 score.

Table 3. Significant Correlations between PHQ-15, PHQ-9, and HIT-6
Table 3. Significant Correlations between PHQ-15, PHQ-9, and HIT-6


This study shows that a large number of women in a sub-specialty headache clinic in Utah have had sexual, physical and/or emotional abuse. Sexual abuse was the most frequent at 34%. Most of the sexual abuse occurred before the age of 20. The estimated rate of sexual abuse in the general population is 15-25% (Scher, Stewart, Liberman & Lipton, 1998). In chronic headache patients at a specialty clinic, Utah appears to be above this average. Sexual abuse is known to be associated with a poor health status (Leserman, 2005; Walker et al., 1999 as well as more physical symptoms (Tietjen et al., 2007), and a higher utilization of health resources and increased cost to society (Walker et al., 1999). In addition, sexual abuse has been found to be associated with other forms of abuse (physical and emotional) (Dong et al., 2004). In our cohort of 140 patients with some type of abuse, it was common to have other forms as well. We found that almost 21% of the abused women reported all three forms of abuse (sexual, physical and emotional).

As noted in other studies, sexual abuse can occur in any socioeconomic group and education (Swahnberg et al., 2004). In our population, women were from a higher socioeconomic status and had more high school or college experience than our general Utah population.

Headache has been reported to be a major symptom seen in patients who have had sexual abuse. In fact, in one large study of abused women, chronic daily headaches were more than twice as common as in women who were not abused (Felitti, 1991). Early childhood sexual abuse is associated with more headache than in those who have sexual abuse in adulthood (Golding 1999). Chronic headache is associated with depression since 38% of our population had moderate to severe depression. In our population, depression was more severe in those who have had sexual or emotional abuse.

Juang, Wang, Fuh, Lu, and Chen (2004) found that physical abuse in childhood tended to increase the likelihood of chronic daily headache in adolescence. Romans, Belaise, Martin, Morris and Raffi (2002) reported that headache and migraine were definitely correlated with adult physical abuse. Krantz and Ostergren (2000) showed that physical abuse was associated with headache and that women who had physical abuse in childhood or adulthood had an increased likelihood of multiple somatic symptoms In our study, physical abuse was neither associated with headache nor multiple somatic symptoms.

Depression is strongly associated with migraine in patients without abuse. In fact, the prevalence of depression among patients with migraine is 14.7/100,000 vs those who do not have migraine (7/100,000) (Hamelsky & Lipton, 2006). Merikangas, Angst, and Isler (1990) and Breslau et al. (2000) and Breslau et al. (2003) found that those with migraine had three times the incidence of depression than those without migraine. Shared genetic and neuro-biologic factors may link migraine and depression (Silberstein, 2001). Walling et al. (1994a) and Walling et al. (1994b) found that early childhood physical abuse predicted depression, anxiety and somatization. Other studies have also found that women experiencing violence have a significantly higher rate of depression (Nicolaidis, Curry, McFarland & Gerrity, 2004). Depression associated with abuse has also been found to be associated with morbid obesity (Felitti, 1991). Depression was found in 38% of our patients. Depression was increased in our patients with sexual and emotional abuse.

An increase in multiple somatic complaints is similar to other studies of women with all forms of abuse (Tietjen et al., 2007; Krantz & Ostergren, 2000). In our study, 96 (80%) of 120 abused women had a ‘medium’ or ‘high’ level multiple somatic complaints. This finding suggests that women with multiple somatic complaints should also be queried about forms of abuse.

Our headache clinic population is similar in several demographics to the state of Utah. The clinic and general population were not significantly different in race and average number of household members. The clinic patients were significantly more educated (Ȥ2=41.611, p<0.001) and had significantly higher incomes (Ȥ2=30.02, p<0.001) than the general population of the state of Utah. Nevertheless, our study shows that headaches and abuse affects a wide range of individuals even those who are more educated and of higher economic fortune.

We would make the following recommendations for practitioners who see women who have chronic headache. First, the practitioner should ask about abuse in childhood. Recently two questions were found to predict sexual abuse: (a) “When I was growing up, people in my family hit me so hard that it left me with bruises or marks” and (b) “When I was growing up, someone tried to touch me in a sexual way or tried to make me touch them.” (Thombs, Bernstein, Ziegelstein, Bennett & Walker, 2007) These questions had sensitivity 85% and specificity of 88% in predicting sexual abuse. Further, women with multiple chronic health symptoms should also be queried about abuse. Despite many articles about the importance of querying for abuse, only 21% of women with a history of abuse presenting to medical clinics are asked about it (Pearse, 1994).

Treatment for women with headache who have been abused has not been extensively studied. Cognitive behavioral approaches are most frequently used and have the most evidence for success (Leserman, 2005). Behavioral and cognitive therapy are more efficacious in some cases than medications (Payne & Colletti, 1991). Psychotherapy (Martsolf & Draucker, 2005), group therapy (Kessler, White & Nelson, 2003; Talbot et al., 1999), and even inpatient treatment (Stalker, Palmer, Wright & Gebotys, 2005) have been used. No single therapy has been found to be superior, however. In general, finding a single medication that completely stops headache is almost impossible. However, every attempt to reduce the migraine headache with standard preventive medications such as beta blockers, calcium channel blockers, and anti-convulsants should be attempted (Goadsby, Lipton & Ferrari, 2002).

The reason for emotional abuse causing increased rates of headache is not clear. Clearly more work is needed to understand the pathophysiology of increased headache in women with all forms of abuse and to determine the best treatment of these disabling headaches.

There are limitations to our study. We do not address any type of abuse in men. We are using a highly specialized population (those going to a headache clinic) so our findings may not be generalizable to all headache patients. The study also relied on the woman’s recollection of abuse. Nevertheless, this study gives us insight into some women visiting a chronic headache clinic in Utah.


  • Breslau, N., Schultz, L.R., Stewart, W.F., Lipton, R.B., Lucia, V.C., Welch, K.M. (2000). Headache and major depression: is theassociation specific to migraine? Neurology 54(2), 308-13.
  • Breslau, N., Lipton, R.B., Stewart, W.F., Schultz, L.R., Welch, K.M. (2003). Comorbidity of migraine and depression: investigating potential etiology and prognosis. Neurology 60(8), 1308-1312.
  • Domino, J.V., Haber, J.D. (1987). Prior physical and sexual abuse in women with chronic headache: clinical correlates. Headache 27(6), 310-314.
  • Dong, M., Anda, R.F., Felitti, J.J, Dube, S.R., Williamson, D.F., Thompson, T.J., et al. (2004). The interrelatedness of multiple forms of childhood abuse, neglect, and household dysfunction. Child Abuse and Neglect 28(7), 771-784.
  • Emiroglu, F.N., Kurul, S., Akay, A., Miral, S., Dirik, E. (2004). Assessment of child neurology outpatients with headache, dizziness, and fainting. Journal of Child Neurology (5), 332-336.
  • Felitti, V.J., Long-term medical consequences of incest, rape, and molestation. (1991). Southern Medical Journal 84(3), 328-331.
  • Golding, J.M. (1999). Sexual assault history and headache: five general population studies. Journal of Nervous and Mental Disease 187(10), 624-629.
  • Goadsby, P.J., Lipton, R.B., Ferrari, M.D. (2002). Migraine–current understanding and treatment. New England Journal of Medicine 346(4), 257-270.
  • Hamelsky, S.W., Lipton, R.B. (2006). Psychiatric comorbidity of migraine. Headache 46(9), 1327-33.
  • Headache Classification Subcommittee of the International Headache Society. (2004). The International Classification of Headache Disorders: 2nd edition. Cephalalgia 24 (Supplement 1), 9-160.
  • Howard, F.M. (1995). Abuse history and chronic pain in women: I. Prevalences of sexual abuse and physical abuse. Obstetrics and Gynecology 85(1), 158-159.
  • Hilden, M., Schei, B., Swahnberg, Kl, Halmesmaki, E., Langhoff-Roos, J. et al. (2004). A history of sexual abuse and health: a Nordic multicentre study. British Journal of Obstetrics and Gynecology 111(10),1121-1127.
  • Juang, K.D., Wang, S.J., Fuh, J.L, Lu, S.R., Chen, Y.S., (2004). Association between adolescent chronic daily headache and childhood adversity: a community-based study. Cephalalgia 24(1), 54-59.
  • Kessler, M.R., White, M.B., Nelson, B.S. (2003). Group treatments for women sexually abused as children: a review of the literature and recommendations for future outcome research. Child Abuse and Neglect 27(9), 1045-1061.
  • Krantz G., Ostergren, P.O., (2000). The association between violence victimisation and common symptoms in Swedish women. Journal of Epidemiology and Community Health 54(11), 815-821.
  • Kosinski, M., Bayliss, M.S., Bjorner, J.B., Ware, J.E. Jr., Garber, W.H., Batenhorst, A., et al. (2003). A six-item short-form survey for measuring headache impact: the HIT-6. Quality of Life Research 12(8), 963-974.
  • Kroenke, K., Spitzer, R.L., Williams, J.B. (2001). The PHQ-9: validity of a brief depression severity measure. Journal of General Internal Medicine 16(9), 606-613.
  • Kroenke, K., Spitzer, R.L., Williams, J.B. (2002). The PHQ-15: validity of a new measure for evaluating the severity of somaticsymptoms. Psychosomatic Medicine 64(2), 258-266.
  • Leserman, J. (2005). Sexual abuse history: prevalence, health effects, mediators, and psychological treatment. Psychosomatic Medicine 67(6), 906-915.
  • Lipton, R.B., Stewart, W.F., Diamond, S., Diamond, M.L., Reed, M. (2001). Prevalence and burden of migraine in the United States: data from the American Migraine Study II. Headache, 41(7), 646-657.
  • Martsolf, D.S., Draucker, C.B. (2005). Psychotherapy approaches for adult survivors of childhood sexual abuse: an integrative review of outcomes research. Issues in Mental Health Nursing 26(8), 801-825.
  • Merikangas K.R., Angst, J., Isler H. (1990). Migraine and psychopathology. Results of the Zurich cohort study of young adults. Archives of General Psychiatry 47(9), 849-853.
  • Nicolaidis, C., Curry, M., McFarland, B., Gerrity, M. (2004). Violence, mental health, and physical symptoms in an academic internal medicine practice. Journal of General Internal Medicine 19(8), 819-827.
  • Payne, T.J., Colletti, G. (1991). Treatment of a 15-year-old girl with chronic muscle-contraction headache using implosive therapy. British Journal of Medical Psychology 64(Pt 2), 173-177.
  • Pearse, W.H. (1994). The Commonwealth Fund Women’s Health Survey: selected results and comments. Womens Health Issues 4(1), 38-47.
  • Roberts, S.J. (1996). The sequelae of childhood sexual abuse: a primary care focus for adult female survivors. Nurse Practitioner 21, 42-52.
  • Romans, S., Belaise, C., Martin, J., Morris, E., Raffi, A. (2002). Childhood abuse and later medical disorders in women. An epidemiological study. Psychotherapy and Psychosomatics 71(3),141-150.
  • Scher, A.I., Stewart, W.F., Liberman, J., Lipton, R.B. (1998). Prevalence of frequent headache in a population sample. Headache 38(7), 497-506.
  • Silberstein, S.D., Lipton, R.B. (2000). Chronic daily headache. Current Opinion in Neurology. 13(3), 277-283.
  • Silberstein, S.D. (2001). Shared mechanisms and comorbidities in neurologic and psychiatric disorders. Headache 41(Supplement 1), S11-S17.
  • Stalker, C.A., Palmer, S.E., Wright, D.C., Gebotys, R. (2005). Specialized inpatient trauma treatment for adults abused as children: a follow-up study. American Journal of Psychiatry 162(3), 552-559.
  • Stewart, W.F., Lipton, R.B. (1993). Migraine headache: epidemiology and health care utilization. Cephalalgia 13 (Supplement 12), 41-46.
  • Swahnberg, K., Wijma, B., Schei, B., Hilden, M., Irminger, K., Wingern, G.B. (2004). Are sociodemographic and regional and sample factors associated with prevalence of abuse? ACTA Obstetricia et Gynecoloica Scandinavica 83(3), 276-288.
  • Talbot, N.L., Houghtalen, R.P, Duberstein, P.R., Cox, C., Giles, D.E., Wynne, L.C. (1999). Effects of group treatment for women with a history of childhood sexual abuse. Psychiatric Services 50(5), 686-692.
  • Thombs, B.D., Bernstein, D.P., Ziegelstein R.C., Bennett, W., Walker, E.A. (2007). A brief two-item screener for detecting a history of physical or sexual abuse in childhood. General Hospital Psychiatry 29(1), 8-13.
  • Tietjen, G.E., Brandes, J.L., Digre, K.B., Baggaley, S., Martin, V., Recober, A., et al. (2007) High prevalence of somatic symptoms and depression in women with disabling chronic headache. Neurology 68(2), 134-140.
  • Walker, E.A., Gelfand, A., Katon, W.J., Koss, M.P., Von Korff, M., Bernstein, D., et al. (1999a). Adult health status of women with histories of childhood abuse and neglect. American Journal of Medicine 107(4), 332-339.
  • Walker, E.A., Unutzer, J., Rutter, C., Gelfand, A., Saunders, K., VonKorff, M., et al. (1999b). Costs of health care use by women HMO members with a history of childhood abuse and neglect. Archives of General Psychiatry 56(7), 609-613.
  • Walling, M.K., O’Hara, M.W., Reiter, R.C., Milburn, A.K., Lilly, G., Vincent, S.D. (1994a). Abuse history and chronic pain in women: II. A multivariate analysis of abuse and psychological morbidity. Obstetrics and Gynecology 84(2), 200-206.
  • Walling, M.K., Reiter, R.C., O’Hara, M.W., Milburn, A.K., Lilly, G., Vincent, S.D. (1994b). Abuse history and chronic pain in women: I. Prevalences of sexual abuse and physical abuse. Obstetrics and Gynecology 84(2), 193-199.

Labor Induction Trends in Utah and a Comparison of Maternal and Neonatal Outcomes among Induced Deliveries without an Identified Medical Indication


Induction of labor is a valuable obstetric procedure when indicated by a medical or clinical condition. However, strong debate surrounds the issue of non-medical inductions that are conducted for convenience, and whether or not the benefits outweigh the risks. This research focuses on trends in induction and assesses maternal and neonatal outcomes associated with labor induction, specifically those inductions conducted without identifiable medical indications. In this study, Utah birth certificate records from 1992 to 2005 were used to examine trends. Maternal and neonatal outcomes related to the induction of labor without an identified indication were assessed using only 2005 birth certificate data. When comparing neonatal outcomes, induced and non-induced deliveries were quite similar. However, nulliparous women with induced labor were significantly more likely to have instrumental procedures used to assist with vaginal delivery compared to the non-induced group (22.8% vs. 17.7 %). It is the recommendation of this study that women receive a complete disclosure of the risks and benefits associated with the induction of labor before undergoing this obstetric procedure. Future studies are needed to understand why Utah’s induction rate is higher than the national rate.


Induction of labor is a valuable obstetric procedure when initiated for a medical reason. For several clinical conditions, the decision to induce labor may be appropriate and lifesaving for mother and child. Although induction of labor has been practiced for many years, the procedure has become more widely used in recent years. Nationally and in Utah, induction rates doubled between 1992 and 2005. However, large proportions of inductions are performed in the absence of any medical or obstetric indication and are considered “elective.”

According to the American College of Obstetricians and Gynecologists (ACOG), induction of labor is undertaken when, in the opinion of the physician, the risks of delivery to the mother or the fetus or both, are less than the risk of continuing the pregnancy (ACOG, 1999).

Controversy exists regarding the potential benefit of elective induction at term. Proponents of elective induction argue that they are avoiding potential adverse outcomes associated with postdates, preeclampsia and term intrauterine fetal death of unknown causes (Martin et al., 1978). It was suggested by Macer et al. (1992) that elective induction allows for better planning by the physician, patients, and their families. The anxiety of some women may be reduced by the assurance that their personal physician may be present during the birth of their child. Others advocate elective induction to allow for daytime deliveries with a rested patient and optimal perinatal medical care personnel (Smith et al., 1984). Those opposing elective induction would argue that not only is it generally not recommended by ACOG, but also it is an unnecessary and unnatural process (Macer et at., 1992). There is concern over inducing labor before fetal lung maturity has been achieved (ACOG, 1999).

A number of studies have examined the associations between elective induction and pregnancy outcomes. Although inconsistent, the results are compatible with an association between elective induction and increased risk of cesarean delivery. Some studies have observed this increased risk among all women (Prysak et al., 1998; Glantz, 2005) while others have observed it only among nulliparous women (Seyb et al, 1999; Dublin et al, 2000). Many studies have found that patterns of labor progression differ between women who are induced and those who are not (Hoffman et al., 2006; Vahratian et al., 2005). A higher rate of instrumental delivery has also been observed among induced women compared to those experiencing spontaneous labor (Dublin et al., 2000; Smith et al., 1984). Women who were induced tended to receive greater numbers of intrapartum interventions, such as epidural anesthesia, compared to women experiencing spontaneous labor (Glantz, 2005; Smith et al., 1984). Some research has calculated higher than average length of stay in maternity units among induced women (Vrouenraets et al., 2005; Glantz, 2005), as well as higher delivery costs (Maslow et al., 2000). Other studies found no adverse impact associated with the induction of labor. Smith et al. (1984) found that when careful patient selection is made by an experienced clinician, planned delivery does not jeopardize the outcomes of either the mother or fetus compared to spontaneous labor. This result was similar to that of Cole et al. (1975) who found no evidence that elective induction of labor increased fetal or maternal morbidity.

The purpose of this study was to assess maternal and neonatal outcomes associated with the induction of labor among low risk women who lacked identifiable indications for induction at term.


Data Sources: To examine induction trends, Utah birth certificate records from 1992 through 2005 were used. Induction of labor was measured by birth certificate item ‘induction’ and identifies all deliveries where induction of labor was attempted, regardless of whether the induction was successful. On the birth certificate record, induction is defined as the initiation of uterine contractions before the spontaneous onset of labor by medical and/or surgical means for the purpose of delivery. Excluded from the study were records of births where stimulation or augmentation of a previously established labor was indicated. The birth certificate does not distinguish between elective and indicated inductions, but it does contain information on most of the medical indications related to induction. Induction rates per 100 live births in Utah were compared with overall U.S. rates.

Maternal and neonatal outcomes related to the induction of labor without an identified indication were assessed using only 2005 birth certificate data.

Study Selection Criteria: The study included women with singleton births clinically estimated to be between 38-40 completed weeks’ gestation. The clinical estimate of gestational age on the birth record is defined as the age in total weeks completed from the last menstrual period date to the date of delivery. Gestational age parameters 38-40 weeks were selected based on a review of the parameters used in recent induction research to identify a low-risk group. The study was also limited to women who gave birth in a hospital. In order to define infants in vertex presentation, women with breech/malpresentations were excluded. To further limit the study to low-risk women, records with one or more listed medical risk factors for pregnancy were excluded. Many of the risk factors in the birth certificate records are recognized by ACOG as indications for induction, and include: pregnancy induced hypertension, premature rupture of membrane, Rh sensitization, acute or chronic lung disease, chronic hypertension, polyhydramnios/oligohydramnios, pre-existing diabetes, gestational diabetes, renal disease, and eclampsia. Examination of previous pregnancy history resulted in the removal of women with previous preterm, macrosomic, or SGA infants, since history of such conditions may point toward an increased risk for similar complications. The remaining group was further reduced to exclude those with certain complications of pregnancy. The complications excluded for were: placenta previa, abruptio placenta, umbilical cord prolapse, incompetent cervix, uterine bleeding, cephalopelvic disproportion, and genital herpes. Several of these listed complications are defined by ACOG as contraindications for induction, and, as such, disqualify the subjects from being considered ‘low risk’. Women diagnosed as febrile were excluded from the study on the basis of the suggestion that the condition could be considered a proxy for “chorioamnionitis”, which is also a recommended indication for induction by ACOG (MacDorman et al., 2002). The final step in defining the study population was to remove all birth records where the mother was indicated to have had any previous cesarean delivery. This final study population was divided into two groups: those induced and those non-induced, in order to compare maternal and neonatal outcomes. The flowchart of selection of study participants is presented in Figure 1.

Figure 1: Selection of Study Participants
Figure 1: Selection of Study Participants

Study Participants: During 2005, there were 51,517 resident births in Utah. Of these, only 38,153 women who delivered at a hospital with a single infant in vertex presentation in the gestational age range of 38-40 weeks were initially included for this study. The application of exclusion criteria resulted in a total of 14,809 women as the final study population. Among these, 5,945 women had labor induced and were compared with 8,864 non-induced women.

Outcomes: Maternal outcome was measured in terms of incidence of cesarean and instrumental delivery. Instrumental delivery was defined as any use of either forceps or vacuum during a vaginal delivery. Neonatal outcomes of interest included birth weight, Apgar scores at 1 and 5 minutes, the presence of moderate/heavy meconium, birth injury, fetal distress, hyaline membrane disease/ RDS, or assisted ventilation.

Statistical Analysis: The analyses performed included descriptive summary statistics, chi square, t-test, and regression. Multivariate logistic regression mod-els were developed to estimate the effect of induction on the risk of cesarean and instrumental delivery while adjusting for potential confounders. Adjusted odds ratios (OR) with 95% confidence interval were generated from regression models. All analyses were performed using SAS version 9.1 (SAS Institute Inc., Cary, NC, USA).


Trend Data: The overall induction (indicated and non-indicated) rate in Utah increased from 16.4% in 1992 to 35.3% in 2005. This represents a 115% increase. Utah’s rate is significantly higher than the national average (33.6% vs. 21.2%, 2004 data). The trends in induction rates in Utah and the U.S. are presented in Figure 2.

Figure 2: Induction Rates, Utah vs. United States, 1992-2005
Figure 2: Induction Rates, Utah vs. United States, 1992-2005

Assessment of Outcomes

Characteristics of Participants: Shown in Table 1 are selected maternal characteristics of women who underwent induction of labor compared with those whose labor was not induced. Women with induced labor were slightly older and had more education compared to the non-induced group. A difference was also noted in the proportion of nulliparous women, which was lower in the induction group compared with the non-induction group (30.3% vs. 42.2%). The induction group had a higher proportion of married women compared to the non-induced group (87.4% vs. 82.1%).

Induction of Labor and Maternal Outcomes: The primary maternal outcomes measured in this study were the risk of cesarean section or instrumental delivery associated with labor induction. A comparison of induced and non-induced women delivering infants by various modes is presented in Table 2.

Table 1: Characteristics of Women by Induction Status
Table 1: Characteristics of Women by Induction Status
Table 2: Comparison of Mode of Delivery
Table 2: Comparison of Mode of Delivery

This study revealed slight differences in cesarean rates between the induced and non-induced group. The primary c-section rate for the induction group was significantly lower compared to the non-induced group (4.1% vs. 5.8%, p< .001). Overall, the use of instruments associated with vaginal delivery was similar in both groups (10.4% vs. 10.0%). However, when analyzed by parity, nulliparous women in the induction group had a significantly higher instrumental delivery rate compared to the nulliparous in the non-induced group (22.8% vs. 17.7%, p<.001; see Table 3).

Table 3: Mode of Delivery by Parity
Table 3: Mode of Delivery by Parity

Since instrumental delivery among nulliparous women was correlated with birth weight and maternal age, as well as induction, we used a logistic regression model to adjust for these potentially confounding characteristics. Instrumental delivery was designated as the dependent variable in the logistic model, with group (induction vs. non-induction) as an independent variable, and birth weight and maternal age as covariates. The odds ratio for instrumental delivery adjusted for these confounding factors is shown in Table 4. The nulliparous women in the induced group were 1.36 times more likely to experience instrumental delivery compared to the nulliparous women in the non-induced group, regardless of maternal age or newborn’s birth weight.

Table 4: Risk of Instrumental Delivery among Nulliparous Women Related to Induction
Table 4: Risk of Instrumental Delivery among Nulliparous Women Related to Induction

Neonatal Characteristics: Neonatal characteristics at birth are presented in Table 5. The average neonatal weight at birth in the labor induction group was 3,416 grams compared with 3,365 grams in the non-induced group (p<.05). In the induced group, a higher proportion of newborns were macrosomic (≥ 4,000 g) compared to newborns in the non-induced group (6.5% vs. 5.8%, p <.05). The prevalence of low birth weight (<2,500 g) neonates were slightly lower in the induced group compared to the non-induced group (0.6% vs. 1.0%, p<.05). There were no significant differences in Apgar scores of less than 7 at either 1 or 5 minutes between the induced and non-induced groups.

Table 5: Neonatal Characteristics at Birth
Table 5: Neonatal Characteristics at Birth

Neonatal Outcomes: Neonatal outcomes associated with induction are provided in Table 6. The proportion of newborns with birth injury did not differ significantly between the induced and non-induced group (1.1% vs. 1.3%). This study observed that meconium staining occurred more frequently among the non-induced group compared to the induced group (7.1% vs. 3.6%, p<.001). No significant difference in the proportion of newborns with hyaline membrane disease/RDS, assisted ventilation, or fetal distress was observed.

Table 6: Neonatal Outcomes Associated with Induction of Labor
Table 6: Neonatal Outcomes Associated with Induction of Labor

Time and Day of Delivery: In 2005, the majority of induced deliveries (80%) occurred between 8 AM and 8 PM, compared to 60% among the non-induced (see Table 7). Women who had labor induced were also more likely to deliver on weekdays (Monday – Friday) compared to the weekend, with a preponderance Tuesday – Thursday (see Figure 3).

Table 7: Time of Delivery
Table 7: Time of Delivery
Figure 3: Delivery by Day of the Week
Figure 3: Delivery by Day of the Week


Induction rates are increasing rapidly both locally and nationally. Increases were seen among women with documented medical indications as well as among women with elective inductions (Yeast et al., 1999). Explanation of the dramatic increase in the incidence of labor induction is certainly complex and may be comprised of numerous contributing factors (Rayburn et al., 2002; Zhang et al., 2002). A suggested primary reason for the rising usage of induction centers on the ability it provides to plan the timing of birth for the physician, patient, and family. Other explanations include the increasing availability of effective cervical ripeners and medical liability concerns associated with continued expectant management, particularly post-term (Rayburn et al., 2002). In addition, the ability to more accurately determine the gestational age of the neonate, and more sophisticated techniques of antepartum fetal surveillance may also contribute to the rising induction rate (Yeast et al., 1999).

In assessing maternal outcomes using 2005 birth certificate data, this study found that the cesarean delivery rate was lower among the induced group compared to the non-induced group. This finding is consistent with the findings of Cole et al. (1975). However, other previous studies have documented an increased rate of cesarean delivery with elective induction, particularly among the nulliparous (Macer et al., 1992; Smith et al., 1984; Yudkin et al., 1979).

In this study instrumental delivery rates did not differ between the induced and non-induced groups overall. This parallels the finding of Cole et al. (1975), where forceps use was similar in both groups of women, those induced and those experiencing spontaneous labor. Their study also found that the use of epidurals is more commonly associated with elective induction than with women experiencing spontaneous labor. Therefore, it has been hypothesized that it may be epidural analgesia rather than induction that is the causal factor explaining the higher incidence of instrumental delivery among induced women. Wigton et al. (1994) also noted that patients receiving epidurals were more likely to require instrumental delivery. When they controlled for the influence of epidurals, in their analysis, they found no difference in instrumental delivery rates between induced and non-induced groups. This study was unable to control for epidural use because of the unavailability of data. While no differences in instrumental delivery rates were observed in this study between the induced and non-induced groups, when parity was introduced, an increased risk of instrumental delivery was observed among nulliparous women (OR = 1.36, 95% CI 1.18 – 1.58). This is of concern since research has documented a link between instrumental delivery and maternal morbidity such as soft tissue injury/discomfort, maternal hematoma, and pelvic floor injury. Vacuum extraction may also “result in significant fetal injury if misused;”, problems such as cephalohematoma, subgaleal hematoma, intracranial hemorrhage, hyperbilirubinemia, and retinal hemorrhage may result (ACOG, 2000).

Comparison of neonatal outcomes showed that women with induced labor without an identified indication had, on the average, infants with higher birth weights. These findings are in accordance with those of Macer et al. (1992). In this study no association was observed between induction of labor and birth injury. However, previous studies, particularly research done by Dublin et al. (2000), found birth injuries were more common among infants born to women whose labors were induced. The greater prevalence of meconium staining among the non- induced group in this study population, was consistent with the findings of previous studies (Dublin et al., 2000; Smith et al., 1984), who found that meconium was present much less frequently in the electively induced group. The findings of no association between induction and low Apgar scores (<7) were also consistent with previous studies (Dublin et al., 2000; Macer et al., 1992; Smith et al., 1984). Overall, in this study, the neonatal outcomes between the induced and non-induced groups were similar.

This study found that the majority of induced women were delivered on weekdays in the afternoon or early evening hours. By contrast, the deliveries of non-induced or spontaneously laboring women were distributed evenly over the 24-hour period. These findings parallel those reported in other studies (Macer et al., 1992; Smith et al., 1984). In this study women who had labor induced were found to be more likely to deliver on weekdays. This may support the hypothesis that a primary attraction of induction is the opportunity it provides to choose a convenient delivery time.

Several limitations may be noted in this study. The birth certificate contains information on maternal medical risk factors, labor complications, and induction of labor, however, it does not distinguish between elective induction and medically indicated induction. This study assumed that women without medical risk factors and certain selected labor complications may be defined as low-risk, healthy women undergoing induction. It is possible that women may have had other mitigating factors not reported on the birth certificates, such as joint pain, back pain, edema, indigestion, distance from hospital, or psychosocial issues that influenced the physician’s decision for induction. Such information may be present in medical charts or in other medical records.

Another limitation is that some information of potential interest in assessing induction of labor is not included in birth certificate data. This information includes items such as Bishop’s score for cervical ripening, the different methods of induction, use of epidural analgesia, and length of labor. It is possible that the associations observed in this study between the induction of labor and various maternal and neonatal outcomes may be linked with particular methods of induction only, as mentioned by Dublin et al. (2000). There were also no intrapartum or postpartum complications recorded on the birth certificate, such as hemorrhage, laceration, etc. Incomplete information regarding medical history remains an important limitation of this study and warrants caution in the interpretation of these findings. It is possible that there were other differences between women with induced labor and those with non-induced labor that were unable to be measured in this study.

In conclusion, overall maternal and neonatal outcomes were not adversely affected by induction among low-risk women who lacked an identified indication. However, induction was associated with increased risk for instrumental delivery among nulliparous women in this study. Therefore, it is recommended that all women receive full disclosure of the benefits and risks associated with induction before undergoing this obstetric procedure. Further studies need to be undertaken as Utah’s induction rate is significantly higher than the national rate.


  • American College of Obstetricians and Gynecologists, (ACOG). (June 2000). Operative vaginal delivery. ACOG Practice Bulletin, Clinical Management Guidelines for Obstetrician-Gynecologists. No. 17. pp. 417-424. 
  • American College of Obstetricians and Gynecologists, (ACOG). (1999). Induction and augmentation of labor. ACOG Technical Bulletin. No. 10, 562-568. 
  • Cole, R.A.; Howie, P.W.; Macnaughton, M.C. (1975, April 5). Elective induction of labor. The Lancet. 767-770.
  • Dublin, S; Lydon-Rochelle, M.; Kaplan, R.C.; Watts, D.H.; Critchlow, C.W. (October 2000 ). Maternal and neonatal outcomes after 
  • induction of labor without an identified indication. American Journal of Obstetrics and Gynecology, Vol. 183(4): 986-994. 
  • Glantz, J.C. (April 2005). Elective induction vs. spontaneous labor association and outcomes. Journal of Reproductive Medicine. Vol. 50(4), 235-240. 
  • Hoffman, M.K.; Vahratian, A.; Sciscione, A.C.; Troendle, J.F.; Zhang, J.. (2006, May). Comparison of labor progression between induced and noninduced multiparous women. Obstetrics & Gynecology. Vol. 107(5), 1029-1034. 
  • Macer, J.A.; Macer, C.L.; Chan, L.S. (1992). Elective induction versus spontaneous labor: A retrospective study of complications and outcome. American Journal of Obstetrics and Gynecology. Vol. 166, 1690-1697. 
  • MacDorman, M.F.; Mathews, T.J.; Martin, J.A.; Malloy, M.F. (2002). Trends and characteristics of induced labour in the United States, 1989-98. Paediatric and Perinatal Epidemiology . Vol. 16, 263-273. 
  • Martin, D.H.; Thompson, W.; Pinkerton, J.H.M.; Watson, J.D. (1978). A randomized controlled trial of selective planned delivery. British Journal of Obstetrics and Gynecology. Vol. 85, 109-113. 
  • Prysak, M.; Castronova, F.C. (1998, July). Elective induction versus spontaneous labor: A case-control analysis of safety and efficacy. Obstetrics and Gynecology. Vol. 92, No. 1, 47-52. 
  • Rayburn, W.F.; Zhang, J. (2002, July). Rising rates of labor induction: Present concerns and future strategies. Obstetrics and Gynecology. Vol. 100, No. , 164-167. 
  • Seyb, S.T.; Berka, R.J.; Socol, M.L.; Dooley, S.L.. (1999). Risk of cesarean delivery with elective induction of labor at term in nulliparous women. Obstetrics & Gynecology. Vol. 94: 600-607. 
  • Smith, L.P.; Nagourney, B.A.; McLean, F.H.; Usher, R.H. (1984, March). Hazards and benefits of elective induction of labor. American Journal of Obstetrics & Gynecology. Vol. 148(5), 579-585. 
  • Vahration, A.; Zhang, J.; Troendle, J.F.; Sciscione, A.C.; Hoffman, M.K. (2005, April). Labor progression and risk of cesarean delivery in electively induced nulliparas. Obstetrics & Gynecology. Vol. 105(4), 698-704. 
  • Vrouenraets, F.P.J.M.; Roumen, F.J.M.E.; Dehing, C.J.G.; Van den Akker; Aarts, M.J.B.; Scheve, E.J.T. (2005, April). Bishop score and risk of cesarean delivery after induction of labor in nulliparous women. Obstetrics & Gynecology. Vol.105(4), 690-697. 
  • Wigton, T.R.; Wolk, B.M. (1994, January). Elective and routine induction of labor. The Journal of Reproductive Medicine. Vol. 39, No. 1, 21-26. 
  • Yeast, J.D.; Jones, A.; Poskin, M. (1999). Induction of labor and the relationship to cesarean delivery: A review of 7001 consecutive inductions. American Journal of Obstetrics and Gynecology. Vol. 180, No. 3, Part 1, 628-633. 
  • Yudkin, P.; Frumar, A.M.; Anderson, A.B.M.; Turnbull, A.C. (1979, April). A retrospective study of induction of labour. British Journal of Obstetrics and Gynaecology. Vol. 86, No. 4, 257-265. 
  • Zhang, J.; Yancey, M.K.; Henderson, C.E. (2002). U.S. national trends in labor induction, 1989-1998. Journal of Reproductive Medicine. Vol. 4, 120-124. 


We thank Brenda Ralls PhD, Sharon Talboys, MPH, Karen Zinner, MPH, and Tara Johnson, MS for their valuable comments about data analysis and interpretations.

Periodontal Disease and the Risk of Adverse Pregnancy Outcomes (Part 1: A Review of Current Literature)


During the last decade numerous investigators have studied the posited relationship between periodontal disease in pregnant women and adverse pregnancy outcomes such as premature labor, pre-term deliveries, small-for-gestational age infants, early or late miscarriages, low birth weights and pre-eclampsia. This article presents the results of a comprehensive literature review of these investigations as well as other articles containing similar summaries or commentaries about the studies. The review objective was to ascertain and summarize what the investigators have concluded about this topic. Articles were obtained from the authors’ files, references provided in other publications, articles shared by colleagues, and articles listed in PubMed©, many of which were obtained through interlibrary loans at the University of Utah, Salt Lake City, Utah. The authors identified 67 initial articles. Of those 67, 39 contained original empirical data. Twenty-three of the 39 disclosed positive associations, 5 disclosed no associations, 7 revealed mixed associations (both positive and no associations depending on the variables analyzed). Another 4 articles analyzed, in a preliminary sense, the role of pathogens as potential causal explanations for positive associations. The remaining articles contained summaries or commentaries about previously reported data or impending studies. Despite all of the research that has occurred, clearly there still isn’t sufficient evidence to conclude or explain definitively a causal relationship between periodontitis in pregnancy and adverse pregnancy outcomes. The only definitive conclusion that can be reached is that there is a lot of evidence that women who have had adverse pregnancy outcomes have more of a tendency to have periodontitis than those who do not.


The topic of the posited relationship between periodontal disease (periodontitis) in pregnant women and adverse pregnancy outcomes (premature labor, pre-term deliveries, small-for-gestational age infants, early or late miscarriages, low birth weights and eclampsia or preeclampsia) has received a lot of attention among researchers. During the last decade numerous investigators1-67 have reported or commented on the results of studies focusing on the topic. The majority of the empirical studies (at least twenty-three [3-4, 10, 15, 19, 22, 26, 28-29, 34, 36-38, 40, 43, 47-48, 56, 58, 62, 64-65, 67]), which include a range of methodological approaches and interventions, from prospective case-control studies to retrospective, non case-control studies using convenience samples, demonstrate to one degree or another a positive association between the presence of periodontal disease in pregnant mothers and diverse adverse pregnancy outcomes. This paper is devoted to a comprehensive literature review of the articles pertaining to this topic.

Methodology for Literature Review

Studies analyzed for inclusion in this literature review were identified from various sources: (1) Personal files of the authors. (2) References listed by previous investigators in their published articles. (3) Articles shared among colleagues. (4) Articles listed through PubMed©, a service of the National Library of Medicine and the National Institutes of Health. Copies of many of the articles were obtained through an interlibrary loan service of the University of Utah, Eccles Health Sciences Library, Salt Lake City, Utah.

The current authors read and examined the articles with the objectives of determining their contents in order to categorize them, i.e., empirical vs. non-empirical, positive associations, no associations, mixed results, summaries of previous studies; and to summarize the key findings and significance of disclosed associations. The current authors believe that the literature reviewed in this paper represents a relatively comprehensive list of studies pertaining to the topic as reported in the scientific literature over the last decade. No attempts were made to eliminate any particular periodicals except for those that may have been published in a foreign language for which English translations were locally unavailable. Table 1 is a numerical summary of the articles reviewed.

Table 1. Summary of Number of Articles Reviewed


This section delineates the results of the literature review. Literature is summarized in three categorical areas derived from the review process: (1) Studies Reporting Positive Associations; (2) Studies Reporting No Associations; (3) Studies Reporting Mixed or Equivocal Findings or Summaries of Previous Research Findings.

Studies Reporting Positive Associations

Possibly the first evidence of a positive relationship was reported in 1996 by Offenbacher, et al.[67] A case-control study of 124 pregnant or postpartum mothers, divided into case (preterm low birth weight or PLBW ) and control (normal birth weight or NBW) groups, disclosed worse periodontal disease among the former than the latter. The authors concluded that periodontal disease is a statistically significant risk factor for PLBW.

Other studies were reported in 1998. Davenport, et al.,[65] examined the relationship between maternal periodontal disease and PLBW. In their case-control study of 177 subjects, it was found that the extent and severity of periodontal disease were higher than predicted and may have reflected elevations in gingival inflammation associated with pregnancy.

Dasanayake,[62] in a 1:1 matched case-control study of 55 pairs of pregnant women, in which control variables were introduced, found that mothers of LBW infants were shorter, less educated, married to men of lower occupational status, had less healthy areas of gingival and more areas with bleeding and calculus, and gained less weight during pregnancy. The author concluded that poor periodontal health of the mother is a potential risk factor for LBW.

In another study of 1,313 pregnant women, Jeffcoat, et al.,[58] found that the data showed an association between the presence of periodontal disease at 24 weeks’ gestation and subsequent preterm birth.

In 2001, Offenbacher, et al.,[56] again reported on another five-year prospective study of 814 pregnant women. Their aim was to determine whether maternal periodontitis contributed to the risk for prematurity and growth restriction in the presence of traditional obstetric risk facts. The investigators concluded that the study provided evidence that periodontitis and incident progression are significant contributors to obstetric risk for preterm delivery, low birth weight and low weight for gestational age.
Lopez, et al.,48 conducted a randomized controlled study of 400 Chilean pregnant women with periodontal disease, randomly assigning 200 to an experimental group and 200 to a control group. They found that the incidence of PLBW in the treatment group was 1.8% and in the control group was 10.1%. In fact, periodontal disease was the strongest factor related to PLBW. Other factors significantly associated with PLBW were less than six pre-natal visits and maternal low weight gain.

In 2002, Riche, et al.,[47] reported on their study of 1,020 women, 47 of whom had preeclampsia. They found a strong association between periodontal disease status at enrollment and rate of premature delivery observed among preeclamptic women after adjusting for major risk factors, including maternal race, age, marital status, and use of WIC (women, infants’, children’s’ program) or food stamp services.

To determine if maternal periodontal disease is associated with the development of preeclampsia, Boggess, et al.,[40] studied 1,115 healthy pregnant women. After adjusting for other risk factors, they observed that active maternal periodontal disease during pregnancy is associated with an increased risk for the development of preeclampsia.

In the ensuing years, other studies have followed. Jeffcoat, et al.,[38] conducted a pilot study of 366 women, randomized to one of three treatment groups, and compared with an untreated reference group of 723 pregnant women. They noted that performing scaling and root planing in pregnant women may reduce preterm birth.
Radnai, et al.,[36] conducted a case-control study of postpartum women, 41 in a case group and 44 in a control group. A significant association was found between preterm birth and early localized peridontitis of patients.

A study by Goepfert, et al.,[34] of a convenience sample of 59 women who experienced a spontaneous preterm birth (SPB) at <32 weeks gestation, versus a control group of 36 women who experienced an indicated preterm birth at <32 weeks gestation, versus 44 women who experienced an uncomplicated term birth (TB) was revealing. The SPB group had significantly more extensive periodontitis that the TB group. Moreover, after controlling for maternal age, race, education, insurance status, parity, history of a SPB and smoking, women with severe periodontitis were almost three times as likely to experience a SPB as those without severe periodontitis.

In 2005, Marin, et al.,[26] reported on a study of 152 pregnant women, divided into three groups: healthy, gingivitis and periodontitis. They concluded that periodontal disease in normal Caucasian pregnant women, older than 25 years, is statistically associated with a reduction in infant birth weight.

Another study by Moliterno, et al.,[22] of 151 mothers, 76 in a case group and 75 in a control group, relying upon data from hospital registration records, indicated that periodontitis was a risk factor for low birth weight, similar to other risk factors already recognized by obstetricians.

Coming on the research scene again, Lopez, et al.,[19] reported the results of a randomized control trial of 870 pregnant women from Santiago, Chile. A treatment group of 580 women received periodontal treatment before 28 weeks gestation. A control group of 290 women received periodontal treatment after delivery. The treatment group had significantly reduced PTLBW.

More recently in 2006, Sadatmansouri, et al.,[10] reported the results of clinical trial research of 30 pregnant women (18-35 years of age) with moderate to severe periodontitis, 15 of which receive periodontal treatments and 15 of which did not receive treatments. The authors concluded that periodontal therapy results in a reduction in the PLBW rate.

Results of a prospective study were published by Offenbacher, et al.[4] They studied 1,020 pregnant women who received antepartum and postpartum periodontal examinations. It was found that maternal periodontal disease increased relative risk for preterm or spontaneous preterm births. In fact, periodontal disease progression during pregnancy was found to be a predictor of more severe adverse pregnancy outcome of very preterm birth, independent of traditional obstetric, periodontal and social domain risk factors.

Boggess, et al.,[3] also studied prospectively 1,017 women, risk ratio adjusted for age, smoking, drugs, marital and insurance status and preeclampsia. Their conclusion was that moderate or severe periodontal disease in early pregnancy is associated with delivery of a small-for-gestation-age infant.

Studies Reporting No Associations

At least five [6,21,23,35,42] of the empirical studies reported disclose no evidence of relationships between periodontal disease in pregnant women and adverse pregnancy outcomes.

Davenport, et al.,[42] reported in 2002 the results of a case-control study of 236 pregnant women cases and a daily random sample of 507 controls. They found no evidence for an association between PLBW and periodontal disease. They concluded that the results do not support a specific drive to improve periodontal health of pregnant women as a means of improving pregnancy outcomes.

In 2004, Moore, et al.,[35] completed and reported a prospective study of 3,738 women. They found no significant relationships between the severity of periodontal disease and either preterm or LBW. They observed, however, that there did “appear” to be a correlation between poorer periodontal health and those that experienced a late miscarriage. The major conclusion of the study was that there was no association between either preterm birth or LBW and periodontal disease in the study population.
A study was also conducted by Noack, et al.,[23] and reported in 2005. Of 59 pregnant women with a high risk of LBW (suffering from preterm contractions) versus 42 women with no preterm contractions and infants appropriate for date and weight, there were no significant differences between the groups in any aspects of the studied periodontitis parameters. Periodontitis was not noted to be a detectable risk factor for PLBW in pregnant women.

Also reported in 2005 was a study by Lunardelli and Peres.21 They tested the potential link between periodontal disease in pregnant women and LBW or prematurity. Relying on a population-based, cross-sectional study of 449 parturients in Southern Brazil, they found no association between the variables.

Michalowicz, et al.,[6] sought to study the effect of nonsurgical periodontal treatment on preterm birth. Their 2006 reported study of 823 women included random assignment of 413 patients to a treatment group which received scaling and root planning, compared to 410 patients in a control group which received no treatment. The authors concluded that treatment of periodontitis improves periodontal health and is safe, but does not significantly alter the rates of preterm birth, LBW or fetal growth restriction.

Studies Reporting Mixed or Equivocal Findings or Summaries of Previous Research Findings

The remainder of the published articles we analyzed, [1-2, 5, 7-9, 11-14, 16-18, 20, 24-25, 27, 30-33, 39, 41, 44-46, 49, 50-53, 55, 57, 59, 60-61, 63] both empirical and nonempirical reveal mixed findings, focus in a preliminary sense on the study of the role of antigens or pathogens in explaining the relationship, or provide summary commentary (from other literature reviews) about conclusions derived from studies already conducted. For example, Farrell, et al.,[11] reported mixed findings in their prospective study of 1,793 women reported never previously smoking. There was, in fact, an association between some measures of periodontal disease and late miscarriage, but no association between periodontitis and preterm birth or LBW in the study population.

In an earlier study Moreu, et al.,[24] based on examinations of 96 pregnant women in first, second and third trimester of pregnancy, observed mixed findings. They reported that periodontal disease is a significant risk factor for LBW but not for pre-term delivery.

Buduneli, et al.,[27] evaluated the possible link between periodontal infections and PLBW for post-partum women with low socioeconomic characteristics. They found no statistically significant differences between the cases and the controls regarding dental and periodontal parameters. Bacterial load scores, however, were significantly higher in the controls than in the cases.

Similarly, but conversely, Mitchell-Lewis, et al.,[53] in a study of 213 pregnant women, with 74 assigned to a treatment group and 90 to a non treatment group, found mixed results. They observed no differences in clinical periodontal status between the two groups. However, PLBW mothers had significantly higher levels of certain bacteria.
Some studies are beginning to identify potential pathogens (organisms) and the potential roles they may play in fostering the relationship. Hill (1998),[66] examined the effects of a complex of bacterial vaginosis microbes and their impact of PLBW. The study provided evidence associating maternal periodontal disease with PLBW taken with the isolation of F. nucleatum, Capnocytophaga, and other oral species from amniotic fluid.

Dasanayake, et al.,[52] studied 448 women, predominantly African American and socioeconomically homogeneous, using case and control groups. Their data showed that LBW deliveries were associated with a higher maternal serum antibody level against P. gingivalis at mid-trimester. The association remained significant after controlling for smoking, age lgG levels against other selected periodontal pathogens, and race.

One analytical study in 2001 by Madianos, et al.,[55] of 812 deliveries from a cohort study of pregnant mothers presented measures of maternal periodontal infection using whole chromosomal DNA probes to identify 15 periodontal organisms within maternal periodontal plaque sampled at delivery. A conclusion was proffered: the high prevalence of elevated fetal lgM to C. rectus among premature infants raises the possibility that this specific maternal oral pathogen may serve as a primary fetal infectious agent eliciting prematurity.

A study reported in 2006 by Yiping, et al.,[9] of 34 pregnant women also provided some direct evidence of oral-utero microbial transmission. The authors stated that their observations suggested a Bergeyella strain identified in the patient’s intrauterine infection originated from the oral cavity.

Some of the reported studies mentioned previously have engendered commentary about the reliability and validity of the investigations, some of it controversial about whether some of the results from different studies are in conflict, or and about the need for more skillful appraisals of the methodologies used in the analyses. One commentator, Ahearne,[31] suggested that “the concept of evidence based dentistry is an honorable one, but the reality is that it can become very confusing for the practicing dentist when different studies ask the same question but come up with different answers.” Ahearne first referred to the study by Moore, et al.,[35] in which no positive relationship was found between periodontal disease and pre-term birth or LBW. Secondly, he noted that the very same month Radnai, et al.,[36] asked a very similar question and came to the conclusion that peridontitis was an important risk factor for pre-term birth. The conclusion of the letter was that “if the difference in the outcomes of the studies is due to the difference in the populations studied then, surely it raises some questions about the validity of clinical trials in general.”

In a follow-up research letter, Beckett, et al.,[25] using “a systematic process of critical appraisal, discovered that one of the studies contained a far more reliable evidence source than the other.” They recommended that “practitioners must develop critical appraisal skills. It is important not to fall into the trap of assuming because a paper is published in a referred journal, it must be sound. . . .”

One interesting study contained an insightful meta analysis of previous research. Khader and Ta’ani,[29] in a methodologically sophisticated review of previous studies, utilizing independently abstracted data from the studies, found that periodontal diseases in the pregnant mother significantly increases the risk of subsequent prê-term birth or LBW. Their conclusion was based on two previous case-control studies and three prospective cohort studies that met prestated meta analysis inclusion criteria. Another interesting conclusion was reached: “there is no convincing evidence, on the basis of existing case-control and prospective studies, that treatment of periodontal disease will reduce the risk of pre-term birth.”


The majority of reported studies indicate a positive association between periodontitis in pregnant mothers and adverse pregnancy outcomes. Although a plethora of research has already occurred, clearly there still isn’t sufficient evidence, however, to conclude a causal relationship between the presence of periodontitis and adverse pregnancy outcomes. The only definitive conclusion that can be reached is that there is a lot of evidence of a positive association of periodontitis with adverse pregnancy outcomes. In other words, those women who have had adverse pregnancy outcomes have more of a tendency to have periodontitis than those who do not. This fact is evident even when various control variables are analyzed as potential explanations or reasons for the relationship. The precise mechanisms or chemical processes that would establish a definitive causal relationship have not yet been unequivocally identified. Further research to identify and isolate causal mechanisms or processes still needs to be undertaken. It would be wise to conduct a prospective case-control study in which an adequate sample of subjects is included, and multiple regression is applied to assess the independent contributions (amount of variance accounted for) of various variables that are known to predispose to adverse pregnancy outcomes.

Despite the lack of conclusive causal explanations, proper prophylaxes should still be encouraged. There isn’t any evidence to suggest that proper prophylaxes won’t be beneficial to pregnant women, and it is likely more prudent to err on the side of prevention rather than doing nothing.


  1. Bobetsis, Y.A., Barros, S.P., & Offenbacher, S. (2006). Exploring the relationship between periodontal disease and pregnancy complications. J Am Dent Assoc 137 (Suppl. 2), 7S-13S.
  2. Douglass, C.W. (2006). Risk assessment and management of periodontal disease. J Am Dent Assoc 137 (Suppl. 3), 27S-32S.
  3. Boggess, K.A., Beck, J.D., Murtha, A.P., Moss, K. & Offenbacher, S. (2006). Maternal periodontal disease in early pregnancy and risk for a small-for-gestational-age infant. Am J Obstet & Gynecol 194, 1316-22.
  4. Offenbacher, S., Boggess, K.A., Murtha, A.P., Jared, H.L., Lieff, S., McKaig, R.G., Mauriello, S.M., Moss, K.L., & Beck, J.D. (2006). Progressive periodontal disease and risk of very preterm delivery. Am J Obstet & Gynecol 107, 29-36.
  5. Goldenberg, R.L., & Culhane, J.F. (2006, Nov.). Preterm birth and periodontal disease. N Engl J Med 355(18), 1925-27.
  6. Michalowicz, B.S., Hodges, J.S., DiAngelis, A.J., Lupo, V.R., Novak, M.J., Ferguson, J.E., Buchanan, W., Bofill, J., Papapanou, P.N., Mitchell, D.A., Matseoane, S., & Tschidi, P.A. (2006, Nov.). Treatment of periodontal disease and the risk of preterm birth. N Eng J Med 355(18), 1885-94.
  7. Goldie, M.P. (2006, Aug.). Healthy mother, healthy baby. Int J Dent Hyg 67(6), 162-3.
  8. Nesse, W., Spijkervat, F.K., Abbis, F., & Vissink, A. (2006, May). Links between periodontal disease and general health. 2. Preterm birth, diabetes and autoimmune diseases. Ned Tijdschr Tandheelkd 113(5), 191-6.
  9. Yiping, H., Ikegami, A., Bissada, N., Herbst, M., Redline, R., & Ashmead, G.G. (2006, Apr.). Transmission of an uncultivated bergeyella strain from the oral cavity to the amniotic fluid in a case of preterm birth. J Clin Microbiology 44(4), 1475-83.
  10. Sadatmansouri, S., Sedighpoor, N., & Aghaloo, M. (2006, Mar.). Effects of periodontal treatment phase I on birth term and birth weight. J Indian Soc Pedod Prev Dent 24(1), 23-6.
  11. Farrell, S., Ide, M., & Wilson, R.F., (2006, Feb.). The relationship between maternal periodontitis, adverse pregnancy outcome and miscarriage in never smokers. J. Clin Peridontol 33(2), 115-20.
  12. Vettore, M.V., Sheiham, A., & Peres, M.A. (2006, Feb.). Low birth weight and periodontal diseases association. Rev Saude Publica 40(1), 184-5, 181-2, author reply 185-6, 182-3.
  13. Xiong, X., Buekens, P., Vastardis, S., & Wu, T. (2006). Periodontal disease as one possible explanation for the Mexican paradox. Med Hypoth 67(6), 1348-54.
  14. Xiong, X., Buikens, P., Fraser, W.D., Beck, J., & Offenbacher, S. (2006, Feb.). Periodontal disease and adverse pregnancy outcomes: a systematic review. Brit J Obstet & Gynecol 113(2), 135-43.
  15. Urban, E., Radnai, M., Novak, T., Gorzio, I., Pal, A., & Nagy, E. (2006, Feb.). Distribution of anaerobic bacteria among pregnant periodontitis patients who experience preterm delivery. Anaerobe 12(1), 52-7.
  16. Rajapakse, P.S., Nagarathne, M., Chandrasekra, K.B., & Dasanayake, A.P. (2005). Periodontal disease and prematurity among non-smoking sri lankan women. J Dent Res 84(3), 274-77.
  17. Editor. (2005, Dec.). Periodontal therapy and pregnancy. Br Dent J 199(11), 697.
  18. Mealey, B.L., & Moritz, A.J. (2005, Dec.). Pregnancy and the periodontium. Tex Dent J 122(12), 1204-11.
  19. Lopez, N.J., Da Silva, I., Ipinza, J., & Gutierrez, J. (2005, Nov.). Periodontal therapy reduces the rate of preterm low birth weight in women with pregnancy-associated gingivitis. J Periodontol 76(11 Suppl.), 886-90.
  20. Qureshi, A., Ijaz, S., Syed, A., Quershi, A., & Khan, A.A. (2005, Oct.). Periodontal infection: a potential risk factor for preterm delivery of low birth weight (PLBW) babies. J Pak Med Assoc 55(10), 448-52.
  21. Lunardelli, A.N. & Peres, M.A. (2005, Sep.). Is there an association between periodontal disease, prematurity and low birth weight? A population-based study. J Clin Periodontol 32(9), 938-46.
  22. Moliterno, L.F., Monteiro, B., Figueredo, C.M., & Fischer, R.G. (2005, Aug.). Association between periodontitis and low birth weight: a case-control study. J Clin Peridontol 32(8), 886-90.
  23. Noack, B., Klingenberg, J., Weigelt, J., & Hoffman, T. (2005, Aug.). Periodontal status and preterm low birth weight: a case control study. J Periodontal Res 40(4), 339-45.
  24. Moreu, G., Tellez, L., & Gonzalez-Jaranay, M. (2005, June). Relationship between maternal periodontal disease and lowbirth- weight pre-term infants. J Clin Periodontol 32(6), 622-27.
  25. Beckett, H., Ramsey, R., Thompson, B., & Brennan, P.A. (2005, May). Journal clubs. Br Dent J 198(10), 629.
  26. Marin, C., Segura-Egea, J.J., Martinez-Sahuquillo, A., & Bullon, P. (2005, Mar.) Correlation between infant birth weight and mother’s periodontal status. J Clin Periodontol 32(3), 299-304.
  27. Buduneli, N., Baylas, H., Buduneli, E., Turkoglu, O., Kose, T., & Dahlen, G. (2005, Feb.). Periodontal infections and pre-term low birth weight: a case-control study. J Clin Periodontol 32(2), 174-81.
  28. Jarjoura, K., Devine, P.C., Perez-Delboy, A., Herrera-Abreu, M., D’Alton, M., & Papapanou, P.N. (2005, Feb.). Markers of periodontal infection and preterm birth. Am J Obstet & Gynecol 192(2), 513-9.
  29. Khader, Y.S. & Quteish, T. (2005, Feb.). Periodontal diseases and the risk of preterm birth and low birth weight: a meta-analysis. J Periodontol 76(2), 161-65.
  30. Yeo, B.K., Lim, L.P., Paquette, D.W., & Williams, R.C. (2005, Jan.). Periodontal disease—the emergence of a risk for systemic conditions: pre-term low birth weight. Ann Acad Med Singapore 34(1), 111-6.
  31. Ahearne, J. (2004, Nov.). Evidence based dentistry. Br Dent J 197(10), 594.
  32. Bonett, J.B. (2004, Fall). Exploring the link. Periodontitis and preterm birth. Penn Dent J 2004, Fall, 10-3.
  33. Konopka, T. (2004, May). Periodontitis and preterm low birth weight. Ginekol Pol 75(5), 397-403.
  34. Goepfert, A.R., Jeffcoat, M.K., Andrews, W.W., et al. (2004, Oct.). Periodontal disease and upper genital tract inflammation in early spontaneous preterm birth. Am J Obstet & Gynecol 104(4), 777-83.
  35. Moore, S, Ide, M., Coward, P.Y., Randhawa, M., Borkowska, E., Baylis, R., & Wilson, R.F. (2004, Sep.). A prospective study to investigate the relationship between periodontal disease and adverse pregnancy outcome. Br Dent J 197(5), 251-58.
  36. Radnai, M., Gorzo, I., Nagy, E., Urban, E., Novak, T., & Pal, A. (2004, Sep.). A possible association between preterm birth and early periodontitis: a pilot study. J Clin Periodontol 31(9), 736-41.
  37. Hasegawa, K., Furuichi, Y., Shimotsu, A., Hakamura, M., Yoshinaga, M., & Kamitomo, M. (2003, Dec.). Associations between systemic status, periodontal status, serum cytokine levels, and delivery outcomes in pregnant women with a diagnosis of threatened premature labor. J Periodontol 74(12), 1764-70.
  38. Jeffcoat, M.K., Hauth, J.C., Geurs, N.C., Reddy, M.S., Cliver, S.P., Hodgkins, P.M., & Goldenberg, R.L. (2003, Aug.). Periodontal disease and preterm birth: results of a pilot intervention study. J Periodontol 74(8), 1214-18.
  39. Kadowski, T., Takii, R., Baba, A., & Yamamoto, K. (2003, July). Gingipains as the determinants of periodontopathogenicity. Nippon Yakurigaku Zasshi 122(1), 37-44.
  40. Boggess, K.A., Lieff, S., Murtha, A.P., Moss, K., Beck, J., & Offenbacher, S. (2003, Feb.) Maternal periodontal disease is associated with an increased risk of preeclampsia. Am J Obstet & Gynecol 101(2), 227-31.
  41. Bearfield, C., Davenport, E.S., Sivapathasundaram, V., & Allaker, R.P. (2002, May). Possible association between amniotic fluid micro-organism infection and microflora in the mouth. Brit J Ob Gyn 109(5), 527-33.
  42. Davenport, E.S., Williams, C., Sterne, J., Murad, S., Sivapathasundram, V., & Curtis, M.A. (2002). Maternal periodontal disease and preterm low birthweight: case-control study. J Dent Res 81(5), 313-18.
  43. Lopez, N.J., Smith, P.C., & Gutierrez, J. (2002). Higher risk of preterm birth and low birth weight in women with periodontal disease. J Dent Res 81(1), 58-63.
  44. Otomo-Corgel, J., & Merin, R.L. (2002, Apr.). Periodontol disease and systemic health–what you and your patients need to know. J Calif Dent Assoc 30(4), 307-11.
  45. Rose, L.F., Steinberg, B.J., & Minsk, L. (2002). Periodontal disease and systemic disease. Clinical information for the practicing dentist. J Indiana Dent Assoc 81, 15-18.
  46. Radnai, M., & Gorzo, I. (2002, Dec.). Periodontal disease as a potential risk factor for preterm birth and low birth weight (literature review). Fogorv Sz 95(6), 241-44. (Article in Hungarian).
  47. Riche, E.L., Boggess, K.A., Lieff, S., Murtha, A.P., Auten, R.L., Beck, J.S., & Offenbacher, S. (2002, Dec.). Periodontal disease increases the risk of preterm delivery among preeclamptic women. Ann Periodontol 7(1), 95-101.
  48. Lopez, H.J., Smith, P.C., & Gutierrez, J. (2002, Aug.). Periodontal therapy may reduce the risk of preterm low birth weight in women with periodontal disease: a randomized controlled trial. J Periodontol 73(8), 911-24.
  49. Krejci, C.B., & Bissada, N.F. (2002, Mar.). Women’s health issues and their relationship to periodontitis. J Am Dent Assoc 133(3), 323-9.
  50. McGaw, T. (2002, Mar.). Periodontal disease and preterm delivery of low-birth-weight infants. J Can Dent Assoc 68(3), 165-9.
  51. Teng, Y.T., Taylor, G.W., Scannapieco, F., Kinane, D.F., Curtis, M., Beck, J.D., & Kogon, S. (2002, Mar.). Periodontol health and systemic disorders. J Can Dent Assoc 68, 188-92.
  52. Dasanayake, A.,P., Boyd, D., Madianos, P.N., Offenbacher, S., & Hills, E. (2001, Nov.). The association between porphyromonas gingivalis-specific maternal serum lgG and low birth weight. J Periodontol 72(11), 1491-97.
  53. Mitchell-Lewis, D., Engebretson, S.P., Chen, J., Lamster, I.B., & Papapanou, P.N. (2001). Periodontal infections and pre-term birth: early findings from a cohort of young minority women in New York. Eur J Oral Sci 109, 34-39.
  54. Slots, J, & Kamma, J.J. (2001). General health risk of periodontal disease. Intern Dent J 51(5), 417-27.
  55. Madianos, P.N., Lieff, S., Murtha, A.P., Boggess, K.A., Auten Jr., R.L., Beck, J.E., & Offenbacher, S. (2001, Dec.). Maternal periodontitis and prematurity. Part II: maternal infection and fetal exposure. Ann Periodontol 6(1): 175-82.
  56. Offenbacher, S., Lieff, S., Boggess, K.A., Murtha, A.P., Madianos, P.N., Champagne, C.M.E., McKaig, R.G., Jared, H.L., Mauriello, S.M., Auten Jr., R.L., Herbert, W.N.P., & Beck, J.D. (2001, Dec.). Maternal periodontitis and prematurity. Part I: obstetric outcome of prematurity and growth restriction. Ann Periodontol 6(1), 164-74.
  57. Jeffcoat, M.K., Geurs, N.C., Reddy, M.S., Goldenberg, R.L., & Hauth, J.C. (2001, Dec.). Current evidence regarding periodontal disease as a risk factor in preterm birth. Ann Periodontol 6(1), 183-88.
  58. Jeffcoat, M.J., Geurs, N.C., Reddy, M.S., Cliver, B.S., Goldenberg, R.L., & Hauth, J.C., (2001, July). Periodontal infection and preterm birth results of a prospective study. J Am Dent Assoc 132, 875-88.
  59. Leone, C.R. (2001, Jan-Feb). Maternal periodontal disease and premature birth or low birth weight. J Pediatr (Rio J) 77(1), 6-7.
  60. Engebretson, S.P., Lalla, E., & Lamster, I.B. (1999, Oct.). Periodontitis and systemic disease. N Y State Dent J 65(8), 30-2.
  61. Goldenberg, R.L., Rouse, D.J. (1998, July). Prevention of premature birth. N Engl J Med 339(5), 313-20.
  62. Dasanayake, A.P. (1998, July). Poor periodontal health of the pregnant woman as a risk factor for low birth weight. Ann Periodontol 3(1), 206-12.
  63. Offenbacher, S., Jared, H.L., O’Reilly, P.G., et al (1998, July). Potential pathogenic mechanisms of periodontitis-associated pregnancy complications. Ann Periodontol 3(1), 233-50.
  64. Offenbacher, S., Beck, J.D., Lieff, S., & Slade, G. (1998, Oct.). Role of periodontitis in system health: spontaneous preterm birth. J Dent Educ 62(10), 852-8.
  65. Davenport, E.S., Williams, C.E., Sterne, J.A., Sivapathasundram, V., Fearne, J.M., & Curtis, M.A. (1998, July). The east London study of maternal chronic periodontal disease and preterm low birth weight infants: study design and prevalence data. Ann Periodontol 3(1), 213-21.
  66. Hill, G.B. (1998, July). Preterm birth: associations with genital and possibly oral microflora. Ann Periodontol 3(1), 222-32.
  67. Offenbacher, S., Katz, V., Fertik, G., Collins, J., Boyd, D., Maynor, G., McKaig, R. & Beck, J. (1996, Oct.). Periodontal infection as a possible risk factor for preterm low birth weight. J Periodontol 67(Suppl.), 1103-13.

Periodontal Disease and the Risk of Adverse Birth Outcomes (Part 2: The Results of a Pilot Study)


Preterm birth is the major cause of neonatal mortality and morbidity. Recent studies have suggested that there may be an association between periodontal disease and delivery of preterm and or low birth weight infants. This paper summarizes the results of a pilot study conducted to evaluate the relationship between periodontal disease and preterm low birth weight. This study also explores whether providing clinical preventive periodontal intervention can reduce the risk of adverse birth outcomes. The findings of this evaluation study indicate that there are potential avenues which can be explored to develop a cost analysis for periodontal treatment to be included as a covered benefit for pregnant women.


Preterm birth (PTB) is a major public health problem. The rate of preterm birth has increased significantly in the last decade. In 2004, 12.5% of the births in the U.S. were preterm (i.e., occurred before 37 weeks of gestation) (Centers for Disease Control and Prevention, 2006). Preterm birth and associated low birth weight (PLBW) represent the major causes of neonatal mortality and morbidity, including neurodevelopmental disabilities, congenital anomalies and behavioral disorders (Vohr et al., 2000). It is estimated that, each year, more than five billion dollars are spent in the U.S. for neonatal care, with the majority of this amount consumed in caring for PLBW infants (Khader, 2005).

Although about half of PTBs have no known risk factors linked with them (Iams et al., 2001), there is emerging evidence of the association between periodontal infection and the risk of PLBW. Studies in this area, using a variety of research designs, have resulted in varied findings. Offenbacher et al. (1996) found a statistically significant association between periodontal disease in pregnant women and PLBW infants. The authors determined that mothers with periodontal infection had more than seven times the risk of delivering a PLBW infant, even after adjusting for other potential risk factors. Jeffcoat et al. (2001) also found an association between periodontal infection and PTB. A randomized controlled trial concluded that periodontal disease appeared to be an independent risk factor for PLBW and that periodontal therapy significantly reduced the rates of PLBW in the women with periodontal disease (Lopez et al., 2002). On the other hand, several epidemiologic studies have concluded that there was no association between periodontal disease and birth outcomes (Davenport et al., 2002; Moore et al., 2004).

Previous studies have not assessed the association between periodontal disease and PLBW among the Medicaid population. Hence, this Utah pilot study, using a sample of pregnant women enrolled in Medicaid, was undertaken to: 1) understand the extent of periodontal disease among pregnant women; 2) assess the association between periodontal disease and PLBW; and 3) determine the possible benefits of preventive intervention in reducing the risk of PLBW. This project represented an effort to evaluate the current standard of care provided by Medicaid, and was a collaborative endeavor between Health Care Financing (Medicaid) and the Maternal and Child Health Bureau both part of the Utah Department of Health (UDOH).

Materials and Methods

Study Population

The study population consisted of pregnant women enrolled in Medicaid. Medicaid eligibility for pregnant women in Utah is at 133% of the Federal Poverty Level. Originally this study planned to include three Medicaid Family Dental Plan (FDP) clinics: South Main Clinic in Salt Lake City, Ellis Shipp Clinic in West Salt Lake City, and Provo Clinic. However, during the implementation stage, the study was limited to the South Main dental clinic located in Salt Lake County (the most populous county in Utah). The Institutional Review Board at UDOH reviewed and exempted the study from requiring approval on the basis that the study would serve as a program evaluation “pilot” project. The research group from Medicaid requested that the Department of Workforce Services refer Medicaid eligible pregnant women to this clinic. When women came for their dental visits, they were asked if they would be willing to participate in this pilot study. After the verbal consent was received, the FDP clinic staff administered an intake questionnaire, which included pregnancy history, medical conditions, and demographic information. The completed intake questionnaire containing the subject’s signature served as the final consent for participation in the study. Based on this convenience sample, a total of 460 pregnant women were recruited for this study.

Measurement of clinical periodontal status

The periodontal examination was performed using a tool called a PSRTM (Periodontal Screening & Recording, American Dental Association, 1992). The PSR is a specifically designed periodontal probe that features a 0.5mm balled end and a colored band extending from 3.5 to 5.5mm from the tip. A PSR score is determined by assessing how much of the colored band on the PSR probe is visible when the PSR probe is placed in the gingival crevice. The scoring system ranges between 0 – 4. A detailed description of PSR coding is provided in Chart 1. All study participants received a full mouth periodontal assessment. The mouth was divided into sextants–maxillary right, anterior, and left; mandibular left, anterior, and right–and a numeric score was assigned to each area. A dentist, who had been calibrated prior to the study, conducted all clinical periodontal examinations at the project site.

Chart 1. Description of PSR Coding

The criteria used to determine the presence of periodontal disease were based on PSR scores. Study participants with PSR scores under 3 in all sextants were defined as exhibiting no periodontal disease. Women with a score of 3 or greater in one or more sextant(s) were diagnosed as having periodontal disease.

Study intervention

After the periodontal assessment, the study participants were screened for intervention eligibility. Only pregnant women between 22 and 26 weeks gestation with periodontal disease were eligible to receive preventive clinical intervention or periodontal treatment. The intervention in this study consisted of dental prophylaxis, including rubber cap polish and periodontal deep scaling. Those women with periodontal disease who received periodontal treatment were defined as the “intervention” group. The intervention group also received instruction in oral hygiene. Those women who were diagnosed with periodontal disease, but who did not return to the clinic to receive the periodontal treatment or did not receive treatment within the 22-26 week window, were defined as the “non-intervention” group. During the planning stage of the study, an anticipated 30% no-show rate for the dental prophylaxis treatment was anticipated. Group designation was recorded in each subject’s treatment chart. The same examiner performed all examinations and measurements.

Data Collection

The recruitment of study participants was done over a three-year period (October 2003 to September 2006) at the South Main project site. Socio-demographic information, pregnancy and medical history were collected at baseline by a structured intake questionnaire. This collection of information was followed by a clinical full-mouth periodontal examination where a PSR score was recorded. The FDP clinic staff reminded participants of their scheduled periodontal intervention appointments. PSR scores and the types of interventions given were recorded on the subject’s treatment form.
Information on labor/delivery, birth outcome and health of the newborn were collected from birth certificate data. All intake questionnaires and treatment forms were provided to UDOH by the project site dental clinician for data entry and linkage with birth certificate data.

Study Outcomes

Gestational age and birth weight were selected as the main birth outcome characteristics of interest. Additionally, birth outcome characteristics were further subdivided into several categories: preterm (<37 weeks gestation), extreme preterm (<32 weeks gestation), low birth weight (LBW, <2,500 g), very low birth weight (VLBW, <1,500 g), and PLBW (<37 weeks gestation and <2,500g). Birth outcomes were determined by linking dental clinic data (intake and treatment forms) with birth certificate data. The calculation of gestational age at delivery was based on the clinical estimate of gestation recorded on the birth certificate. This clinical estimate on the birth record is defined as the age in total weeks completed from the last menstrual period date to the date of delivery.

Statistical Analyses

The dental clinic data were merged with birth certificate 2003-2006 data. Since the birth certificate 2006 data were not finalized at the time of analysis, preliminary 2006 birth data (available through Medicaid Data Warehouse) were used for this pilot study. Linkage was performed in multiple cycles using both deterministic and probabilistic approaches. Analyses for this study included descriptive statistics, chi squared tests, t-tests and logistic regression. All analysis was performed using SAS version 9.1.


A total of 460 pregnant women were recruited from the FDP clinic to participate in this pilot study. These dental clinic data were merged with birth certificate data. Deterministic linkage generated 403 matched records from the possible 460 dental clinic records. Use of mother’s name, date of birth (DOB), and infant delivery date generated an additional 14 matched records, yielding a total of 417 cases. Forty-three cases were unmatched due to incomplete information (missing DOB and names), miscarriages, or fetal deaths. Women with multiple gestations were excluded from the analysis. A total of 400 women with singleton births were included in the final study sample. Table 1 summarizes the characteristics of the study participants. The majority (71.7%) of the study participants were 20-29 years old. About ninety-two percent of the participants were white. Thirteen percent of the study population was of Hispanic/Latina ethnicity. Close to one in five (18.1%) women smoked during pregnancy. More than three-fourths (77.8%) of women began prenatal care during their first trimester. Approximately five percent of women had a history of previous preterm birth.

Table 1. Demographic Characteristics of Study Participants

A summary of the periodontal disease status of study participants based on PSR scores is presented in Table 2. PSR scores of 0-2 indicate a gingival pocket depth of less than 3.5 mm, and were considered as absence of periodontal disease. Scores of 3-4 indicate a pocket depth of at least 3.5 mm or greater, and were considered as indication of the presence of periodontal disease. More than a third (40.5%) of the participants was diagnosed with periodontal disease.

Table 2. Periodontal Disease Status

Women participating in the study diagnosed with periodontal disease were eligible to receive a clinical preventive intervention between 22-26 weeks’ gestation. Of the 162 women with periodontal disease, 108 women received the intervention. The remaining 54 women with periodontal disease who did not receive intervention became the comparison group against which to evaluate the birth outcomes and benefits of the interventions. Table 3 provides the demographic characteristics, and the pregnancy and medical history characteristics of both intervention and non-intervention groups. The average ages of intervention and non-intervention groups were similar. However, there was a significant difference in educational levels between the groups. The intervention group had a higher proportion of women with education beyond high school compared to the non-intervention group (33% vs. 21%, p=.05). The non-intervention group contained a higher percentage of nulliparous women and smokers than the intervention group, although these differences were not statistically significant. Eight women in the intervention group had a history of preterm birth compared to only one in the non-intervention group. The data illustrate that a higher proportion of women in the non-intervention group had urinary tract infections and bacterial vaginosis compared to women in the intervention group, but the differences were not statistically significant. In both groups, all women with infections had treatment, as reported on the intake form.

Table 3. Characteristics of Intervention and Non-Intervention Groups

In order to assess the relationship between periodontal disease and adverse birth outcomes, analysis included women with no periodontal disease (PSR code <2) and those with periodontal disease who received no intervention. We excluded the women with periodontal disease and who received periodontal treatment from this particular analysis. The comparisons of birth outcomes are presented in Table 4. The rates of PLBW were slightly higher among women with periodontal disease (non-intervention group) compared to women without periodontal disease (5.3% vs. 3.9%), however, these differences were not statistically significant even controlling for the effects of smoking. The data shows that there were no significant associations between periodontal disease and adverse birth outcomes (preterm, low birth weight, or preterm low birth weight).

Table 4. Periodontal Disease and Birth Outcomes

The impacts of periodontal treatment and associated birth outcomes are shown in Table 5. Infants in the intervention group had a higher average gestational age (38.6 ±2.1 vs. 38.3 ±1.9) and a higher average birth weight (3251.8 ±573.7 vs. 3193.8 ±493.9) than in the non-intervention group, but the differences were not significant. Neither preterm nor extreme preterm categories were significantly different when both groups were examined. This pattern was also observed for LBW and VLBW categories. It is possible that the lack of significant differences in birth outcomes, between the intervention group and the non-intervention group, may be attributed to small numbers rather than the effect of periodontal treatment. Interpretations of results are difficult due to these small numbers.\

Table 5. Impacts of Periodontal Treatment


Preterm birth in Utah is of great concern to public health professionals, because preterm infants are at significant risk for serious and lasting health problems. In 2005, of the 51,517 live births in Utah, 10% were preterm. Among the total Medicaid population the preterm rate was higher, at 11%. The state singleton preterm birth rate was 8%, while the Medicaid rate was close to 10%.

The average costs associated with one preterm infant range from $8,000 to more than $70,000 (UDOH, 2005). Based on 2005 hospital discharge data, $165 million were spent statewide on the care of preterm infants. The Medicaid population accounted for 39% of premature births (n=1,981) and consumed more than $63 million (UDOH, 2005). The costs of caring for these numbers of preterm infants are staggering, both in terms of immediate health care dollars and long-term impacts on families and society.

While the economic expense associated with PLBW infants is huge, the cost of providing thorough periodontal intervention is modest. The cost of periodontal treatment that includes dental prophylaxis, scaling, and root planing averages from approximately $32 to $1,000 per patient. Even if providing such periodontal intervention to pregnant women had only modest impacts on the incidence of preterm birth, the economic savings would be immense.

The UDOH conducted this pilot project as a program management/program evaluation study for the purpose of optimizing service delivery. One of the purposes of this study was to understand the extent of periodontal disease among the Medicaid population of pregnant women in Utah. It was found that more than one third (41%) of women referred for dental care to the study site were diagnosed as having periodontal disease. This study also found no statistically significant association between periodontal disease and risk of PLBW. The data indicated that the periodontal intervention did not significantly alter rates of PLBW.

There are important limitations to keep in mind as the results of this pilot study are compared to those of other studies. The study population was based on a convenience sample without any randomization applied. It consisted only of pregnant women who appeared at the Salt Lake County South Main FDP clinic for dental care and who were willing to participate in this study. Initially this study was planned to include multiple dental clinicians in three FDP clinics. However, this pilot study was only implemented in one site. The participation of only one clinic site greatly prolonged the time required to gather adequate data for analysis. This situation placed an extra burden on one site and limited the possibility of generalizing the findings of the study to the entire Medicaid pregnant population in Utah. The small numbers of women in the intervention and non-intervention groups, made it unfeasible to control for potentially confounding factors. Larger numbers of cases are necessary to provide more reliable estimates of statistical significance.

The results of the pilot study may not be comparable with those of other studies due differences in clinical preventive interventions. Other studies have often included plaque control, scaling, and root planing as preventive interventions (Lopez et al., 2002; Offenbacher et al., 1996). In this UDOH study, rubber cap polish and periodontal deep scaling were offered as interventions. Root planing was not offered. The criteria for the diagnosis of periodontal disease also vary from study to study.

The optimal time for providing dental care to pregnant women for maximum effectiveness in impacting preterm birth is unknown. It is possible that periodontal intervention was delivered too late in pregnancy for maximum impact on birth outcome. Studies have varied in terms of the timing of interventions. Some offered the interventions before 20 weeks’ gestation, while others offered interventions before 35 weeks’. The window of intervention for this study was set between 22-26 weeks. The recommendation made by Michalowicz et al. (2006, p.1893) appears wise, that additional studies are needed to determine “whether the provision of periodontal treatment even earlier in pregnancy or before conception might improve birth outcomes.”

A portion of our study population received antibiotics during pregnancy as treatment for infections. Such antibiotic treatment can confound the effects of periodontal interventions (Jeffcoat et al., 2001; Michalowicz et al., 2006). We were unable to control for type of treatment due to lack of data.


Although the present study disclosed no association between periodontal disease and adverse birth outcomes, other research has established possible connections between oral bacteria and systemic diseases, including PLBW. Hence, it is advisable for public health professionals, clinical practitioners, and health care policy makers to make optimal dental care available to all pregnant women. As a means of prevention, it is prudent for pregnant women to be screened for periodontal disease and referred to periodontal specialists in order to avoid the potential for unfavorable birth outcomes. All pregnant women, and women considering pregnancy, should have dental check-ups, including a gingival evaluation. Dental visits during pregnancy provide an ample opportunity to educate women about the importance of oral health both to their own overall health, and to the overall health of their children. Since the emotional and financial costs of prematurity are immense, caution would recommend easy access to periodontal care for all pregnant women. Such a recommendation is consistent with the health guidelines for pregnant women suggested by the Baby Your Baby and Mind Your Mouth programs at the UDOH. The findings of this evaluation study indicate that there are potential avenues which can be explored to develop a cost analysis for periodontal treatment to be considered for inclusion in a benefits package for pregnant women. Preventive interventions have been shown to be more cost effective than treatment.

In the future, further study using a scientifically oriented research design would be prudent. It would provide an opportunity to address the uncertainties raised by the limitations of this pilot study.


  1. American Dental Association and The American Academy of Periodontology. (1992). Periodontal screening & recording. Retrieved December 19, 2005, from
  2. Centers for Disease Control and Prevention. (2006). Births: Final data for 2004. National Vital Statistics Reports. Vol. 55, No. 1. 1-102.
  3. Davenport, E.S.; Williams, C.; Sterne, J.; Murad, S.; Sivapathasundram, V.; Curtis, M.D. (2002). Maternal periodontal disease and preterm low birthweight: Case-control study. J Dent Res, Vol. 81(5), 313-318.
  4. Iams, J.D.; Goldenberg, R.L.; Mercer, B.M. (2001). The preterm prediction study: Can low-risk women destined for spontaneous preterm birth be identified? American Journal of Obstetrics and Gynecology. Vol. 184, 652-655.
  5. Utah Department of Health, Center for Health Data, Indicator-Based Information System for Public Health website: (2005). Inpatient hospital discharge query module for Utah counties and local health districts. Retrieved on January 4, 2005.
  6. Jeffcoat, M.K.; Geurs, N.C.; Reddy, M.S.; Cliver, S.P.; Goldenberg, R.L.; Hauth, J.C. (2001, July). Periodontal infection and preterm birth. Journal of the American Dental Association, Vol. 132, 875-880.
  7. Khader, Y.S.; Quteish, T. (2005, February). Periodontal diseases and the risk of preterm birth and low birth weight: A meta-analysis. Journal of Periodontology. Vol. 76(2), 161-165.
  8. Lopez, N.J.; Smith, P.C.; Gutierrez, J. (2002). Periodontal therapy may reduce the risk of preterm low birth weight in women with periodontal disease: A randomized controlled trial. Journal of Periodontology, Vol. 73, No. 8, 911-924.
  9. Michalowicz, B.S; Hodges, J.S.; DeAngelis, A. J.; Lupo, V.R.; Novak, M.J.; Ferguson, J.E.; Buchanan, W.; Bofill, J.; Papanou, P.N.; Mitchell, D.A.; Matseoane, S.; Tschida, P.A. (2006). Treatment of periodontal disease and the risk of preterm birth. New England Journal of Medicine. Vol. 355, No. 18, 1885-1894.
  10. Moore, S.; Ide, M.; Coward, P.Y.; Randhawa, M.; Borkowska, E.; Baylis, R.; Wilson, R.F. (2004). A prospective study to investigate the relationship between periodontal disease and adverse pregnancy outcome. British Dental Journal, Vol. 197, No. 5, 251-258.
  11. Offenbacher, S.; Katz, V.; Fertik, G. (1996). Periodontal infection as a possible risk factor for preterm low birth weight. Journal of Periodontology, Vol. 67, 1103-1113.
  12. Vohr, B.R.; Wright, L.L.; Dusick, A.M. (2000). Neurodevelopmental and functional outcomes of extremely low birth weight infants in the National Institute of Child Health and Human Development Neonatal Research Network, 1993-1994. Pediatrics. Vol. 105, 1216-1226.

Prescription Drug Use by Women and Men in Utah Medicaid


Substance use and abuse is a factor of great concern to health care stakeholders. The objective of this study was to characterize pharmaceutical prescription utilization among female compared to male Utah Medicaid patients.

  • Analgesics, SSRIsa, anticonvulsants, and gastric acid secretion reducers were the drug classes with the highest fill rates among female patients covered by Medicaid in Utah
  • The majority of patients used multiple prescription drugs throughout the study period
  • The drug class with the highest cost was the antipsychotics, which had a per-patient cost for female patients at only 40% of that for male patients
  • Contrary to what was expected based on previous research, the overall per-patient prescription drug cost was not higher among females versus males
  • There were differences in drug utilization between age groups; most drug classes showed increasing utilization and cost with increasing age

Background and Introduction

Substance abuse has been formulated as one of the leading health indicators in the Healthy People 2010 framework (U.S. Department of Health and Human Services, 2000). Differences in prescription medication use patterns between males and females have been documented by Roe, et al in a retrospective database analysis of 1,294,295 members of a large pharmacy benefit manager (Roe, McNamara, & Motheral, 2002). Investigators found that compared to men in the United States women generally utilize more medications. This finding has also been demonstrated worldwide (Obermeyer et al., 2004). Our goal was to evaluate the status of drug usage by women and compare it to that of the men in the Utah Medicaid prescription claims database.

Study Procedures

All prescription data for adult patients age 18 and above who were covered for at least 6 months and who filled at least one prescription between January 2005 and September 2006 were used. 70% of the patients were female. Patients were divided by gender and age; age categories were grouped as 18-29, 30-39, 40-49, 50-59, and 60+ years. For each drug classb, the proportion of patients that filled at least one prescription within the study period was calculated by gender and age. The top 15 drug classes for each gender-specific age group were reported. The study plan is summarized in Figure 1.

Figure 1. Outline of Study Plan



Of all patients eligible for the Medicaid drug plan for at least 6 months during the study period (101,013) 86% were included in this analysis, because they had at least one drug fill during the study period.

Figure 2. Percentage of female or male drug users in each age group. 60+ shows all patients over 60, 65+ shows all patients over 65.
Figure 3. Gender distribution in each age group.

Patients between 18 and 29 years constituted the largest group both for women (41%) and men (28%), as shown in Figure 2. 23% of the female patients over 60 and 28% of the male patients over 60 were not older than 64.

Overall, males made up 30% of the study population. However in the age classes between 40 and 59 there was a higher proportion of males (39.5% for the 40 to 49 years old patients and 36.9% for the 50 to 59 year olds) than in the other age groups. The lowest rate of males was found in the 18 to 29 year age group (see Figure 3). This was not surprising given that Medicaid recipients differ in several aspects as the existing entry barriers will favour different populations from one or the other gender.

Absolute Consumption of High Use Drug Classes

Analgesics and narcotics were the drug classes with the highest fill rates and the highest number of users in both gender groups, followed by non-steroidal anti-inflammatory drugs (NSAIDs). The drug classes with the highest cost overall were the anti-psychotics and anticonvulsants.

Figure 4. Comparison between the male (n= 25,976 – upper graph) and the female (n=61,006 – lower graph) study population for three absolute consumption indicators (fills/month, cost, number of patients) for the 15 most used drug classes.

The drug classes used by the highest number of pati ents were analgesics, NSAIDs, and selective serotonin reuptake inhibitors (SSRIs) among women and the analgesics, NSAIDs, and gastric acid secretion reducers among men. The most obvious difference between men a nd women in terms of the ranking of drug classes was the use of contraceptives by women (overall rank 12) and the use of thyroid hormones, ranking as the 7th most used drug class among women. Men displayed a relatively higher use of anti-psychotics, anti-hypertensives, and insulin (see Figure 4).

Consumption of High Use Drug Classes Relative to Female or Male Population

Although in absolute numbers, women in the Utah Medicaid prescription database had much higher utilization compared to men, the picture changed when looking at the number of fills per drug class and per patient (see Figure 5). The highest number of fills was registered for the class of analgesics with 4 fills per patient among males and 4.7 fills per patient among females. These numbers correspond to 67% of females and 49% of males having fills for an analgesic (see Figure 6). Anticonvulsants, with 2.3 fills per patient among females and 3.4 fills per patient among males, corresponded to 19 and 23% of female or male patients taking a drug from this class.

Although NSAIDs were associated with a fill rate of 1.7 among females and 1.1 among males, about 48% of females and 31% of males had at least 1 prescription for NSAIDs. Antipsychotic drugs were filled 2.4 times per male patient and 16% of males had at least one fill for an antipsychotic; this was higher than in the female population, which only had 1.1 fill per patient and only 9% had at least 1 fill for an antipsychotic.

Figure 5. Fills per female or male with at least one drug fill in 21 months.
Figure 6. Share of female or male patients with at least one fill in a drug class in 21 months for the most used drug classes.

While analgesics were the highest utilized class by the largest number of patients, they were not the most costly. The per-patient cost associated with analgesics was U.S.$186 for females and U.S.$219 for males). Antipsychotic medications had the highest cost per patient at U.S.$ 690 for males versus U.S.$ 278 for females (see Figure 7). This was followed by anticonvulsants at U.S.$391 for males versus U.S.$242 for females. Among females, antipsychotics and anticonvulsants had the highest cost per patient.

The complete ranking for cost in relation to female or male or all Rx users is listed in the table below:

Table 1. Annual drug cost per user female or male Rx user in Utah Medicaid 2005/2006.

Age-Related Consumption of High Use Drug Classes in the Female Population

Among females, the average number of fills per patients within each class was calculated by age group (see Figure 8). The class with the largest number of fills per pati ent was antipsychotics, with 14.3 fills per patient among patients age 50 to 59. Analgesics, anticonvulsants, thyroid hormones and insulin also had per-patient fill rates of more than 10 in this age group.

There was an increasing number of fills per patient with increasing age in most drug classes up to age 59. There was a drop in fill rates among patients over age 60, most likely due to the fact that a large percentage of that group was only covered by Medicaid for the first 12 months of the study period. In January 2006, with the introduction of Medicare Part D, many patients over age 65 years were no longer covered by Medicaid.

We also found that some drug classes were used more among younger women (e.g. contraceptives) while others were used more among older patients (e.g. antihypertensives, insulins, bone resorption suppressants etc.).

Figure 8. Fills per female with at least one fill of the drug analysed by each age group (missing columns indicate that the drug class was not among he 15 high use drug class in that age group.)

Cost per Female by Age Group

The average cost per patient for each drug class is shown in Figure 9. In general, cost per patient tended to increase with increasing age. For example, the per-patient cost of antipsychotics among patients age 18-29 was U.S.$93.70 and among patients age 50-59 was U.S.$623.40 – an increase by a factor of 7.6. is phenomenon can be explained by both higher fill rate per user (see Figure 8) and an increased percentage of patients using this drug class (see Figure 10).

Figure 9. Cost in U.S.$ per female Rx user of the top drug classes in each age group.
Figure 10. The share of women in different age groups using the top drug classes.

The antipsychotics class was associated with the highest per-patient cost reaching a cost level comparable to that of the overall male population among females age 50 to 59 (U.S.$690 per patient; see Figure 7)

The cost of anticonvulsants, analgesics, and gastric acid secretion reducers started at U.S.$149, 62, and 54 per patient among women age 18 to 29, and increased to U.S.$431, 380, and 372 per patient among women age 50 to 59.


Analgesics were the drug class with the highest number of fills for women and men as well as the highest percentage of the study population using them (see Table 2). SSRIs ranked higher for women and anti-psychotics higher for men. The latter, however, had the highest cost impact for both genders.

In a study on prescription drug use and expenditure in California, analgesics were also the most used drug class with 5.3% of the total population having prescriptions (Bymark & Waite, 2001). There are some striking differences between the Utah Medicaid population and the California general population:

  • In the California study, antihypertensives (ACE inhibitors, CCBs, beta-blockers) all ranked very high, while none of them was among the ten most used drugs in the Utah Medicaid female population
  • Amoxicillin antibiotics were ranked 5 in the Californian study, but did not appear among the highest 15 in Utah
  • In the California study, contraceptives (rank 4) and hormone replacement therapy (rank 10) are much more prominent, even in the general population, than among females in the Utah Medicaid population. In Utah, contraceptives were ranked 12 and hormone replacement was only among the top 15 classes among females between 50 and 59. This high variation may be explained, at least in part, by general cultural differences between populations in the 2 states. In addition, California instituted a program, known as the Family Planning, Access, Care and Treatment Program (Family PACTc ) in 1997 that promotes access to contraceptives for low income families with the goal of preventing unwanted pregnancies and their consequences.
Table 2. Ranking of drug classes by fill rate, percentage of population using them or cost.

It is interesting to note that the percentage of patients using any single drug class in the California study was much lower in our analysis; for example, in California 5.3% of the population had prescriptions for analgesics, compared to 58% of Utah patients. This may be due to the fact that we only calculated usage rates among patients who received at least one prescription, while the California study reported rates among the total population. In addition, we can assume that the overall drug use in a Medicaid population with typically low income and high percentages of chronically ill people will deviate from that of a general mix population. The observation that contraceptives and hormone replacement therapy only make a minor contribution to the drug related gender differences is in line with the observations of Roe et al (Roe, McNamara, & Motheral, 2002).

In an analysis by the Agency for Healthcare Research and Quality (AHRQ) of prescription data from the general outpatient population, investigators found that 44.2% of the population bought at least one central nervous system agent (including analgesics), 37.5% bought a cardiovascular agent, 36.9% bought any kind of hormone, 22% an anti-hyperlipidemic and 20.1% a psychotherapeutic agent (Stagnitti, 2006). These were the 5 drug classes producing the highest cost in the general population.

It has been shown by several researchers, that women in general utilize more drugs than men, that drug cost are also higher for women, and that the ranking of different drug classes differs between women and men. (Obermeyer et al., 2004; Roe, McNamara, & Motheral, 2002; Stagnitti, 2006)

A ‘Medical Expenditure Panel Survey Prescribed Medicines’ reported that 64% of the total U.S. population had a prescription in 2003. (“2003 Medical Expenditure Panel Survey Prescribed Medicines File”, 2005) It is also reported that a higher percentage of the Medicare population (90%) had prescriptions than the non-Medicare population (60%). It was also seen that women represented 55.5% of the Medicare population and caused 58.5% of the Medicare drug expenditure. The general population was composed of 50% women, but they caused 59% of the drug expenditures. In our study, we see that in relation to the 15 drugs used most in the Utah Medicaid
population, that male patients represent a higher cost per patient than women (see Table 1). Figure 3 also shows that the gender distribution in Utah Medicaid is significantly different from the distribution in the non-Medicaid populations, with only between 23% (age 18 to 29) and 39.5% (age 40 to 49) being male. Therefore, our results are specific for the type of male or female population being covered for pharmaceutical benefits by Utah Medicaid.

This study reported on the drug consumption rates of women in different age categories. While analgesics remained the most used drug class (about 65 % of all patients) in all age groups, some differences were found in the ranking of the other classes between age groups. For most medications, fill rates increased with increasing age (see Figure 8): Those patients using a drug class seemed to use it more often if they were older. One explanation for that could be that persistency increases with increasing age of the patients. The Utah Medicaid data would have to be analysed in more detail to confirm this assumption.


We analysed the prescription claims among in the Utah Medicaid database. The data represent the drug consumption behaviour of a very specific population and cannot necessarily be representative of the general population. In addition, the gender-related findings of this study are restricted to this specific population. For further interpretation, it would be important to understand the demographic, social and health related differences between the female and male populations covered by Utah Medicaid.

In this study drugs were classified according to the Specific Therapeutic Class Code (GC3) published by First Data Bank, Inc. Results may vary if using a different type of classification. For example, different types of antihypertensives will be found in different GC3 groups. If they were pooled into one group, antihypertensives might rank much higher than reported here. For comparability and standardization reasons, we have decided to use the GC3 class without further pooling of data in this study.

Another limitation is related to the changes in the prescription drug coverage for elderly patients. Starting in January 2006, many patients were transferred to the Medicare Part D program and were no longer covered by Medicaid. Therefore, the data for patients over age 60 were only collected for 12 months of the 21 month study period. This time difference for a rather large part of the population (see Figure 3) distorted the results for the group over age 60.


  1. 2003 Medical Expenditure Panel Survey Prescribed Medicines File. (2005). Agency for Healthcare Research and Quality, Rockville, MD. MEPS HC-077A.
  2. Bymark, L., & Waite, K. (2001). Prescription drug use and expenditures in California: Key trends and drivers: California Healthcare Foundation (CHCF).
  3. Obermeyer, C. M., Schulein, M., Hardon, A., Sievert, L. L., Price, K., Santiago, A. C., et al. (2004). Gender and medication use: an exploratory, multi-site study. Women Health, 39(4), 57-73.
  4. Roe, C. M., McNamara, A. M., & Motheral, B. R. (2002). Gender- and age-related prescription drug use patterns. Ann Pharmacother, 36(1), 30-39.
  5. Stagnitti, M. N. (2006). The Top Five Therapeutic Classes of Outpatient Prescription Drugs Ranked by Total Expense for Adults Age 18 and Older in the U.S. Civilian Noninstitutionalized Population 2004. Agency for Healthcare Research and Quality, Rockville, MD. Statistical Brief, 154.
  6. U.S. Department of Health and Human Services. (2000). Health People 2010 2nd ed. With Understanding and Improving Health and Objectives for Improving Health. . Washington, DC: U.S. Government Printing Office.

The Impact of Preventive Care: Public Health Policy Affecting Undocumented Immigrants


The United States is facing increasing rates of immigration and increasing numbers of undocumented immigrants. Immigration reform is a current legislative topic and many different approaches have been proposed. Government officials face challenging decisions regarding immigration regulation and public benefits for undocumented immigrants, particularly health care. Most undocumented immigrants are of Mexican descent and many are women with children. Undocumented immigrants demonstrate poorer health than the general population of the United States, and they access the health care system less frequently, with the exception of childbirth-related hospitalizations. Undocumented immigrants have very little access to preventive care, and are frequently afraid of seeking services for which they are eligible because of the threat of deportation.

A number of recent policies have limited undocumented immigrant access to social services such as health care and have resulted in greater cost for more costly emergency procedures, instead of less costly primary care. Future policies should focus on expanding preventive health care coverage for undocumented immigrants, especially prenatal care for women, since it saves money and prevents severe illnesses that can pose public health risks.


The United States is a large and diverse nation, and it is a challenge for policies to keep up with the needs of the people. Policy regarding the regulation of immigration into the United States has been particularly poor in recent decades, and there has been a lack of a coherent strategy to provide resources for recent immigrants, particularly undocumented immigrants. In the case of immigrant health care, the interaction between policy, access and use of the health care system, and health outcomes is dynamic and complex.

In several settings, public policy has mandated that providers and institutions limit health care services to undocumented immigrants. These regulations have influenced use of health care and health status, which have in turn influenced policy. Immigrants have responded to policy changes that limit their access with fear and have thus delayed accessing services they need, thereby suffering negative health outcomes (Berk, Schur, Chavez, & Frankel, 2000; Marshall, Urrutia-Rojas, Mas, & Coggin, 2005; McGuire & Georges, 2003; Stati, Hurley, & Katz, 2006; Trossman, 2004). These negative health outcomes are perceived in vastly different ways by policy makers and are used to establish or strengthen issue positions. The interplay between these factors is important to understanding what regulations and resources should be instituted, but it is equally important to find information that accurately portrays the status of immigrants and health care in the United States. It has been unclear for decades whether or not undocumented immigrants are draining resources from the health care system and to what extent.

People interested in addressing the problems of immigrant health care are found in many levels of government and in public and private organizations, but it has been uncertain whose responsibility it is to develop a solution. Immigration, a nation-to-nation migration, has been a federal issue, but state and local governments have also
created and advocated a variety of policies in recent years in response to the seeming inability of the federal government to embrace a uniform plan. The uncertain climate leaves undocumented immigrants unsure about their rights to health care and often afraid of using even the resources for which they are eligible. Ambiguous jurisdiction has also created a complex ethical and legal environment for health care providers.

At a time when immigration law is undergoing major reform, politicians and public health officials can obtain a sense of successful strategies in managing health care problems related to undocumented immigrant access by analyzing the policies of the past twelve years. Both qualitative and quantitative studies of these policies have
demonstrated undocumented immigrant access to health care is minimal, that such immigrants are using less health care than U.S. citizens and documented immigrants, and that policies that further limit their access to health care result in negative health outcomes (Berk, Schur, Chavez, & Frankel, 2000; Loue, Cooper, & Lloyd, 2005). Policies that expand undocumented immigrant access to preventive care save money by preventing the need for more costly emergency care, and produce more positive health outcomes (Lu, Lin, Prietto, & Garite, 2000; Marshall, Urrutia-Rojas, Mas, & Coggin, 2005).

Introduction to the Problem of Undocumented Immigration

Composition of United States immigrant population

The United States has always been a country of immigrants, but responding to the needs of increasingly large numbers of new residents has never been more demanding than now. The population of the United States is growing by foreign immigration alone by about 2.8% each year (Weis et al., 2001), and the number of undocumented immigrants coming into the United States is sharply increasing (Rehm, 2003). An immigrant who comes to the United States without documents is an illegal alien resident, dwelling within the country illicitly, and this creates administration and record-keeping problems. About 57% of the 10 million undocumented immigrants that currently reside in the United States are from Mexico (Passel, Capps, & Fix, 2004). Immigration policy has thus been directed toward addressing the influx of crossings of the U.S./Mexican border into the United States. These policies have focused on border patrol efforts and stiffer penalties for border crossers, but they have not been successful at slowing the steadily increasing rate of undocumented immigrants who enter the country each year.

More undocumented immigrants are between ages 18-29 compared to the entire Latino population in the United States (Reed, Westfall, Bublitz, Battaglia, & Fickenscher, 2005). They live in higher rates of poverty and have lower levels of education compared to other Latinos and the general population of the United States (Marshall, Urrutia-Rojas, Mas, & Coggin, 2005). Forty-four percent of noncitizen immigrants are uninsured compared with nineteen percent of immigrants who are U.S. citizens (Prentice, Pebley, & Sastry, 2005).

Description of Undocumented Immigrants

In 1993, Governor Pete Wilson of California stated his opposition to public health care funding for undocumented immigrants, even before the introduction of Proposition 187, which he strongly supported. Governor Wilson called for federal legislation to “limit or eliminate the giant magnet of federal incentives that draw foreigners into the county illegally” (Governor Goes Public, 1993). A survey of 972 undocumented Latino immigrants in Fresno, Los Angeles, Houston, and El Paso in 1996-1997 did not support the claim that immigrants come to the United States for free health care and social services. More than half of surveyed immigrants cited jobs/work opportunities as the most important reason they immigrated. The next most common response was to be with family. Less than one percent of respondents considered attaining social services as their primary reason for immigrating. It is unlikely that the respondents would lie about this fact, as they were willing to reveal to interviewers that they were in the country illegally (Berk, Schur, Chavez, & Frankel, 2000).

Undocumented immigrant health status

Minorities, immigrants, and people with low incomes are populations more at risk for “poor physical, psychological, and social health” than other populations, according to the United States Department of Health and Human Services (Marshall, Urrutia-Rojas, Mas, & Coggin, 2005). It has been shown that undocumented immigrants are the U.S. population group with the worst health status, a fact that is generally attributed to their high poverty rates and low levels of education (Marshall et al.). Among the diseases affecting undocumented immigrants are communicable infections such as tuberculosis, incidences of which are higher among recent immigrants to the United States than any other population group (Carvalho et al., 2004; Chin et al., 1998).

Undocumented immigrants also face a variety of conditions harmful to mental health, although there has been little research to show whether or not undocumented immigrants are at higher risk for psychiatric disorders than other people. In a 2005 qualitative study, Sullivan and Rehm identified ten themes of mental health stresses affecting undocumented immigrants: failure to succeed in country of origin; dangerous border crossings; limited resources; restricted mobility; marginalization and isolation; blame/stigmatization; vulnerability/exploitability; fear and fear-based behaviors; stress and depression; and poor health.

Health care usage of undocumented immigrants

According to data from the National Health Interview Survey in 1999, 73 percent of Mexican American children are considered by a parent to be in good health by a parent, compared with 85 percent of non-Hispanic White children (Rehm, 2003). Despite the lower perceived health status, Mexican American children are less likely than any other subgroup to have seen a physician in the last year (Rehm). Rehm argues that these data can be generalized to include both documented and undocumented immigrants. Compared with the entire U.S. population, undocumented immigrants visit physicians less frequently and have lower rates of hospital admission (Berk, Schur, Chavez, & Frankel, 2000). Despite poor health, undocumented immigrants are using the health care system less frequently than most American residents—a fact that refutes the claim that illegal aliens abuse health care privileges. The one exception to the lower rates of health care usage among undocumented immigrants is hospitalizations for childbirth. In the Berk et al. study, 3.4 percent to 6.4 percent of undocumented immigrant women had a childbirth-related hospital visit in the study year. This percentage was far higher than that of the total population (1.7 percent). High rates of childbirth among undocumented immigrants have been attributed to the younger age of undocumented immigrants with respect to the total population and to the fact that children born in the United States will become citizens.

Undocumented immigrants use less health care because they have less access to it, and because they fear deportation. Illegal aliens have less access to health care because of their basic demographic factors: they live in poorer areas and are less educated than other population subgroups (Prentice, Pebley, & Sestry, 2005). They are also ineligible for many services or are bogged down by paperwork that they may not understand to determine eligibility when they attempt to access health care. Undocumented immigrants usually have limited ability to communicate in English, which makes accessing the health care system a daunting task. Many immigrants avoid using services other than emergency benefits, even if the state they live in provides preventive care through Medicaid (Prentice, Pebley, & Sestry, 2005). These immigrants are afraid that use of state resources will make them appear as public burdens and increase their chance of being reported to law-enforcement authorities (Prentice, Pebley, & Sestry, 2005). Changes in federal and state policies about provision of health care services to undocumented immigrants have made it unclear whether immigration status will be required of patients seeking preventive care, and have made illegal aliens reluctant to utilize benefits. One undocumented immigrant said of her fear, “I’m afraid to go out and only go when it’s necessary. If it’s not necessary, I don’t go. I feel impotent, like I can’t do anything.” (McGuire & Georges, 2003).

Impacts of Restricted Health Care Access for Undocumented Immigrants

Prior to 1996, immigrant eligibility for Medicaid services was determined by individual states. States were providing a range of Medicaid services to both documented and undocumented immigrants who qualified for Medicaid based on low income requirements (Loue, Cooper, & Lloyd, 2005). There was a range of preventive care options available in some states, though the policies were certainly not coherent or easy to understand. Many health care providers did not even know what services they were allowed to provide. Under the federal Emergency Medicaid program, emergency services were covered, as long as the immigrants met income-eligibility guidelines (Trossman, 2004). In the early 1990s, the state of California was spending large portions of its state Medicaid funding on services, including Emergency Medicaid services, for undocumented immigrants. With no unified federal policy and little federal funding to address the issue, members of the state government attempted to create their own policy solution. In November 1994, Proposition 187, an initiative to restrict access of undocumented immigrants to any health care funding by Medicaid, was passed by California voters by a narrow margin. The proposition was never enforced, due to multiple court challenges, but it enlivened the national debate as to which health policies would adequately address the problem (Ziv & Lo, 1995).

Proposition 187 was eventually overturned as unconstitutional: states were deemed to have no power to regulate immigration, as it violates the due process clause of the Fourteenth Amendment that guarantees all people equal protection of the laws (Loue, Cooper, & Lloyd, 2005). Opponents of the proposition noted that it was unfeasible to ask physicians and nursing staff to enforce immigration policies in clinics and hospitals. Physicians also contended that requiring them to deny health care to patients in need was against their code of ethics. Proposition 187 also led to fear among immigrants who normally access public health care. In 1995, Ziv and Lo noted that a recent survey of 313 patients with active tuberculosis found that more than one fifth of the patients had no immigration documents. Hesitancy of these illegal immigrants to seek care could have created a serious epidemic of tuberculosis. Laws such as Proposition 187 endanger physician ethics, the health of undocumented immigrants, and public health in general.

Personal Responsibility and Work Opportunity Reform Act

The issue of undocumented immigrant social service use made its way into national Welfare reform legislation in The Personal Responsibility and Work Opportunity Reform Act of 1996 was passed by the United States Congress and became effective on July 1, 1997 (Reed, Westfall, Bublitz, Battaglia, & Fickenscher, 2005). The law regulated cash assistance through the newly named Temporary Aid for Needy Families program and placed more restrictions on eligibility for such assistance. It also introduced a new federal policy regarding Medicaid coverage for immigrants who were not U.S. citizens. Undocumented immigrants were no longer considered eligible for federally funded non-emergency health care services through Medicaid. Documented immigrant eligibility was limited as well. Legal immigrants were only considered federally eligible after five years of residence from the time they received legal status. The legislation included a provision that allowed states to provide non-emergency Medicaid services to immigrants who were federally ineligible if they first passed new state legislation providing the state funding for this purpose. State responses to the Personal Responsibility and Work Opportunity Reform Act (PRWORA) varied. Some cut coverage according to the federal plan, and others, including California, continued Medicaid access, partially in response to the backlash from the plan introduced by Proposition 187.

One of the greatest indicators of the effects of PRWORA is the decreased use of the services for which undocumented immigrants access health care most, namely services related to childbearing, such as prenatal and neonatal care. After the passage of PRWORA, Florida implemented the eligibility restrictions for Medicaid, and thus restricted access to prenatal care, while California did not. In 1999-2001, Fuentes-Afflick et al. interviewed 1,799 postpartum women in California and Florida to compare the effects of the varied implementations of the policy. Three-fourths of undocumented women from California in the study received prenatal care beginning in the first trimester of their pregnancy, whereas only 57% of undocumented women in Florida did. Three times as many undocumented women in Florida received fewer than six prenatal visits, compared to the recommended ten to fifteen. The study demonstrated that the implementation of PRWORA led to decreased use of health care services by undocumented immigrants. It also led to more negative health outcomes for the mothers and infants, including higher rates of low birth weight and premature newborns (Fuentes-Afflick et al.). Prenatal care is a classic example of preventive care that decreases future health problems and the need for more costly secondary care. The United States Department of Health and Human Services notes that, “Adequate access to health care services can improve health outcomes” (Marshall, Urrutia-Rojas, Mas, & Coggin, 2005).

Illegal Immigration Reform and Immigrant Responsibility Act

Attempts by the federal government to limit health care and other public benefits for immigrants were made again in 1996. The Illegal Immigration Reform and Immigrant Responsibility Act of 1996 (IIRAIRA) was enacted on September 30, 1996 (Loue, Cooper, & Lloyd, 2005). In addition to stiffer penalties for fraudulent documents and smuggling persons across the Mexican border, the act placed restrictions on immigrant eligibility for Social Security, Food Stamps, and education, and reiterated the restrictions to health care already in place from PRWORA. Though health care access could be expanded per state determination, the federal government provided block grants for Emergency Medicaid services only. IIRAIRA also required public hospitals to verify patient immigration status, even for emergency services, with the United States Citizenship and Immigration Services (USCIS, formerly the INS) prior to Medicaid reimbursement for such services (Rehm, 2003).

With the implementation of IIRAIRA, the sharing of information between the United States Citizenship and Immigration Services (USCIS) and public hospitals became more prominent. California was no exception to this pattern. Illegal aliens who were accessing emergency health care were thus identified and known by USCIS. Immigrants were frightened by the possibility this created for their personal information to be used in enforcing immigration law against them. A critical care nurse in a hospital that sees large volumes of undocumented immigrants relates:

Undocumented workers often change their names every time they visit the
hospital out of fear. I remember one man was being treated for a seizure that the ER staff initially thought was an isolated event. After talking with him more, I learned that he had come in with a seizure just the month before but had used another name. I’m always telling people that we are hospital workers and here to take care of them, and not immigration (Trossman, 2004).

Loue, Cooper, & Lloyd (2005) examined the accessibility of prenatal care to 157 women of Mexican ethnicity, including 56 women who were undocumented, after the implementation of PRWPRA and IIRAIRA. The illegal aliens were more likely to delay seeking care than their legal resident and citizen counterparts. Fear and confusion about program eligibility requirements for Medicaid services were cited by participants as a reason for being less likely to seek prenatal care.

The impact of decreased access to prenatal care is devastating from a public health and fiscal perspective. Undocumented immigrants who do not receive prenatal care are four times more likely to have low birth weight and preterm infants than those who receive adequate care (Lu, Lin, Prietto, & Garite, 2000). Their infants are also more likely to suffer from abnormal birth conditions such as infant anemia, birth injury, fetal alcohol syndrome, hyaline membrane disease, seizures, and need for assisted ventilation (Lu et al.; Reed, Westfall, Bublitz, Battaglia, & Fickenscher, 2005). California researchers (Lu et al.) calculated that the cost of neonatal care for undocumented immigrants who did not receive adequate prenatal care was $2,341 more than that for an infant whose mother received prenatal care. This cost, as part of labor and delivery services, was covered by the state’s Emergency Medicaid program. The average cost of prenatal care for women in the sample who received it was $702 each. Investigators calculated that, on average, every dollar spent on prenatal care saved $3.33 in neonatal care costs. In addition, care for children who lacked prenatal care continues beyond initial neonatal services. Long-term care for low birth weight babies was $3,247 more for those who had not received prenatal care than for those who had. For every dollar spent on prenatal care, $4.63 in long-term care costs was saved for low birth weight babies. These data argue for expanded coverage of less expensive preventive care rather than denial of services and dependency on more expensive emergency care.

Need for Expanded Health Care Access for Undocumented Immigrants

Preventative Care

It has become a public health priority of the last several decades to expand access to preventive care in order to reduce negative health outcomes. Undocumented immigrants suffer from delay in seeking access to medical care at a higher rate than any other population subgroup (Berk, Schur, Chavez, & Frankel, 2000). They have very
little access to primary care, including dental care. A Missouri Nurses Association member states:

A lot of our patients who are undocumented workers tend to be young-to-middleaged males. For the most part, they are pretty healthy. We tend to see them for episodic illnesses. But dental care is always a problem. There are just not enough dental providers for our clients. And it may take up to six months to get into the dental clinic, so preventive care is virtually non-existent (Trossman, 2004).

Because they lack such access, undocumented immigrants experience more negative health outcomes and utilize expensive emergency services as a temporary fix.

Insurance for undocumented children

Undocumented children remain the most vulnerable subgroup of the immigrant population in the United States. Sixteen percent of undocumented children have not seen a physician in the past two years, compared with seven percent of uninsured white children (Frates, Diringer, & Hogan, 2003). The California Endowment developed a model for providing health insurance for undocumented immigrant children in 2000. The program enrolled thousands of children, and demonstrated increased use of primary care services by such children and their families (Frates et al.), a marker toward future positive health outcomes. This model serves as an example of the direction policy initiatives on immigrant health care should take. Expanded undocumented immigrant health insurance programs would actually save health care money. While some opponents of such an expansion may argue that it would draw more immigrants across the U.S./Mexican border illegally, there are no data to support such a claim. Very few immigrants currently immigrate for the primary purpose of accessing social services, and to assume that their motivations would suddenly change with expanded access to primary health care relies on unfounded logic.


There is no easy solution to the problem of dealing with undocumented immigrants in the United States. In order to create a cohesive policy that meets the needs of the government, health care community, and undocumented immigrants, legislators and public health officials must first understand the nature of the population they are regulating. They need to know what factors truly draw illegal aliens into the United States, specifically whether or not they are seeking public services and particularly free health care above other resources. Policy makers should recognize the demographics and descriptions of the population who are accessing these resources and understand exactly what resources they are using. It is important that public administrators know more about the health and health care usage of illegal immigrants in order to make policy decisions that limit or expand access to care. Finally, it is necessary that policy makers understand the immediate and long-term effects of previous policies. A comprehensive analysis of these historical efforts is an important first step in creating more successful future policy.

The health care system pays a tremendous price to address the needs of this population. The costs of not addressing health care needs, especially with regard to primary and preventive care, are even more significant.Public health efforts to develop primary care access and encourage public use of preventive care should be expanded to undocumented immigrant populations. Instead of making policies that create fear and hesitancy in accessing services, government officials should focus on persuading illegal aliens to use those services that keep them in better health and save money on long-term care.

It is ethically, fiscally, and socially responsible to expand federal coverage of health care for undocumented immigrants. Years of limiting and denying access to health care have led to poorer health outcomes and increased cost. Government officials should look toward program models that fully insure low-income residents of the United States without regard to their immigration status. It is the only policy strategy that works. The best way to ensure the health of all Americans is to see that the issue of health care benefits is addressed in terms of prevention of public health problems, rather than with focus on enforcing immigration laws through the health care system.


  1. Berk, M. L., Schur, C. L., Chavez, L. R., & Frankel, M. (2000). Health Care Use Among Undocumented Latino Immigrants. Health Affairs, 19(4), 51-64.
  2. Carvalho, A. C. C., Saleri, N., El-Hamad, I., Tedoldi, S., Capone, S., Pezzoli, M. C., et al. (2004). Completion of screening for latent tuberculosis infection among immigrants. Epidemiology and Infection, 133, 197-185.
  3. Chin, D. P., DeRiemer, K., Small, P. M., Ponce De Leon, A. P., Steinhart, R., Shecter, G. F., et al. (1998). Differences in Contributing Factors to Tuberculosis Incidence in U.S.-born and Foreign-born Persons. American Journal of Respiratory and Critical Care Medicine, 158, 1797-1803.
  4. Frates, J., Diringer, J., & Hogan, L. (2003). Models and Momentum for Insuring Low-Income, Undocumented Immigrant Children in California. Health Affairs, 22(1), 259-263.
  5. Fuentes-Afflick, E., Hessol, N. A., Bauer, T., O’Sullivan, M. J., Gomez-Lobo, V., Homan, S., et al. (2006). Use of Prenatal Care by Hispanic Women after Welfare Reform. Obstetrics & Gynecology, 107, 151-160.
  6. Governor Goes Public with Fight to Reduce Services States Provide. (1993, August 9). Fresno Bee, p. A12. Library of Congress. (2006, May 26). Legislation Currently in Congress. Retrieved June 10, 2006, from
  7. Loue, S., Cooper, M., & Lloyd, L. S. (2005). Welfare and Immigration Reform and Use of Prenatal Care Among Women of Mexican Ethnicity in San Diego, California. Journal of Immigrant Health, 7(1), 37-44.
  8. Lu, M. C., Lin Y. G., Prietto, N. M, & Garite, T. J. (2000). Elimination of public funding of prenatal care for undocumented immigrants in California: a cost/benefit analysis. American Journal of Obstetrics and Gynecology, 182(1), 233-239.
  9. Marshall, K. J., Urrutia-Rojas, X., Mas, F. S., & Coggin, C. (2005). Health Status and Access to Health Care of Documented and Undocumented Immigrant Latino Women. Health Care for Women International, 26, 916-936.
  10. McGuire, S., & Georges, J. (2003). Undocumentedness and Liminality as Health Variables. Advances in Nursing Science, 26(3), 185- 195.
  11. Passel, J. S., Capps, R., & Fix, M. (2004). Undocumented immigrants: Facts and figures. Retrieved November 23, 2004, from
  12. Prentice, J. C., Pebley, A. R., & Sastry, N. (2005). Immigration Status and Health Insurance Coverage: Who Gains? Who Loses? American Journal of Public Health, 95(1), 109-116.
  13. Reed, M. M., Westfall, J. M., Bublitz, C., Battaglia, C., & Fickenscher, A. (2005). Birth outcomes in Colorado’s undocumented immigrant population. BioMed Central Public Health, 5, 100-107.
  14. Rehm, R. S. (2003). Legal, Financial, and Ethical Ambiguities for Mexican American Families: Caring for Children With Chronic Conditions. Qualitative Health Research, 13(5), 689-700.
  15. Staiti, A., Hurley, R. E., & Katz, A. (2006, February). Stretching the Safety Net to Serve Undocumented Immigrants: Community Responses to Health Needs. Center for Studying Health System Change. Retrieved June 8, 2006, from
  16. Sullivan, M. M., & Rehm, R. (2005). Mental Health of Undocumented Mexican Immigrants: A Review of the Literature. Advances in Nursing Science, 28(3), 240-251.
  17. Trossman, S. (2004, November/December). No easy answers: Addressing the needs of undocumented immigrants. The American Nurse, 3-6.
  18. Weis, S. E., Moonan, P. K., Pogoda, J. M., Turk, L., King, B., Freeman-Thompson, S., et al. (2001). Tuberculosis in the Foreign-Born Population of Tarrant County, Texas by Immigration Status. American Journal of Respiratory and Critical Care Medicine, 164, 953-957.
  19. Young, J., Flores, G., & Berman, S. (2004). Providing Life-Saving Health Care to Children: Controversies and Ethical Issues. Pediatrics, 114(5), 1316-1320.
  20. Ziv, T. A., & Lo, B. (1995). Denial of Care to Illegal Immigrants—Proposition 187 in California. The New England Journal of Medicine, 281, 1215-1220.

Female Refugee Health Status in Utah 2007


What is the definition of a refugee?

“A refugee is any person who is outside his or her country of nationality who is unable or unwilling to return to that country because of persecution or a well-founded fear of persecution.” [1]

There are 59 ethnicities and nationalities represented in the state of Utah. More than 53 languages are spoken in Utah by persons of refugee status[2]. This creates potential and existing communication barriers. To compound this matter, some refugee populations, including the Somali Bantu, did not have a written language in their respective countries. This makes telling time, reading calendars to make appointments, and dispensing health promotion literature ineffective.

Healthcare Coverage

Salt Lake City is one of seventeen refugee resettlement cities in the United States with an International Rescue Committee (IRC) office[3]. All persons of refugee status arriving in Utah start with assistance from the International Rescue Committee or Catholic Community Services (CCS) of Utah; this assistance typically lasts the first six to eight months (with some exceptions). Within the first thirty days of refugee resettlement in Utah, these organizations arrange for each person to have a health screening at the Salt Lake Family Health Center. Appropriate referrals are made to specialists for the various chief complaints and abnormal findings. Each person is given a case manager for the first six months and each family is assigned a primary care provider. Medical expenses are guaranteed under Medicaid for the first eight months and may be continued depending on income and family size. Medicaid covers dental care for children less than 18 years of age and pregnant individuals, but does not cover eye care. Bus passes and other transportation accommodations may be provided for transportation to medical appointments. After the initial eight months, persons of refugee status are referred to Asian Association of Utah, Somali Community Development of Utah, Hartland Partnerships and other community organizations for services.

The Utah Department of Health primarily monitors communicable diseases within the state, which includes those individuals of refugee status. Other health issues such as chronic diseases and reproductive health are not monitored. However, significant key trends were that persons of refugee status arriving from refugee camps tended to have not just more medical needs than the general population, but also more severe medical problems. Many refugees do not seek preventive health care services, indicating reasons such as the “lack of these services in the country of origin, unfamiliarity with these services, and a cultural attitude of seeking health care for symptomatic complaints, not prevention” [4]. This can also increase the use of emergent services.

Figure 1. Current numbers of refugees in Utah. Utah’s refugee demographics by region of origin. 1995-2005. (Department of Workforce Services, p.10, 2006)

Female Refugee Health Status in Utah

Specific information about female refugees is collected differently by the different assistance organizations. In 2006, the International Rescue Committee (IRC) reported 42 female refugees who arrived from Somalia, 36 from Mesh Turk Russia, 17 from Burma, 16 from Cuba, 8 from Sudan, 8 from Congo, 6 from Iran, 5 from Liberia, and 1 from Eritrea.

In 2005, Catholic Community Services (CCS) reported 202 female refugees from the following countries: Congo, Liberia, Ethiopia, Eritrea, Somalia, Sudan, Russia, Cuba, Iran and Iraq. In 2002, CCS reported 247 female refugees from the following countries-Congo, Liberia, Somalia, Sudan, Togo, Bosnia, Serbia, Russia, Iran, Iraq, Lebanon, Afghanistan, Pakistan, and Vietnam.

The International Rescue Committee, Catholic Community Services, Asian Association of Utah, Somali Community Development of Utah (SCDU), and Hartland Partnerships, have noted several important trends in regards to the female refugee health status in Utah: (personal communication Terena Jepson of SCDU December 4, 2006). Among African refugees, especially the Somali Bantu, many women have undergone genital circumcision in their home country as an acceptable cultural procedure. This practice can create health issues that need to be handled with cultural sensitivity and necessitate educating women about its risks. Depression and post traumatic stress disorder are noted in this population due to the stressors of fleeing a war torn country, poor conditions in refugee camps, and possible abuse. Knowledge deficits related to contemporary American practices such as general hygiene necessitate health education.

Positive efforts, like the Health Access Project and Hartland Partnerships, are being made to connect female refugees with accessible healthcare, but improvements can be made. Increased attention to issues surrounding reproductive health are needed. Increased educational outreach efforts to help refugees better comprehend organ systems and not just symptoms are also needed. Classes on nutrition and immunizations are desired to reach more mothers and or care providers.


  1. Center for Disease Control and Prevention. (2006, November 28). Frequently Asked Questions: Domestic Refugee Health Program FAQs. Immigrant, Refugee and Migrant Health. Retrieved December 10, 2006, from
  2. Department of Workforce Services. (2006, November 13). An Introduction to Refugee Resettlement. Refugee Working Group. Retrieved December 10, 2006, from
  3. International Rescue Committee. (2007). IRC Worldwide. Retrieved January 31, 2007, from
  4. National Diabetes Education Program. (2003). Focus Group Observations on Diabetes in Southeast Asians. 2003. Retrieved April 4,2007, from

Utah and U.S. Women’s General Demographics


In 2005, Utah had a household population of 2.4 million equally distributed among women and men. The overall median age was 28.5 years. Thirty percent of the total population was under 18 years and 8 percent was 65 years and older. In 2005, the United States had a household population of 288.4 million 51% females and 49% males. The overall median age was 36.4 years. Twenty-five percent of the total population was under 18 years and 12% was 65 years and older. Based on the total 2005 female population in Utah the distribution was 25.2% for age birth-14, 46.3% for the reproductive ages of 15-44 and 28.5% of women over 44 years of age. The U.S. distribution tended toward an older population with only 20.1% age birth-14, 41.1% reproductive age and 38.8% over 44 years of age.[1]

The overall racial distribution among Utah women is White (93.8%), Asian (2.0%), American Indian/Alaska Native (1.3%), two or more races (1.3%), Black or African American (0.9%) and Native Hawaiian or Other Pacific Islander (0.7%). The overall racial distribution among U.S. women is White (74.3%), Black or African American (12.8%), Asian (4.4%), two or more races (1.9%), American Indian/Alaska Native (0.8%) and Native Hawaiian or Other Pacific Islander (0.1%). Women of Hispanic origin make up 10.1% all females in Utah and 13.9% nationally.[1]


The percent of Utah women over age 17 with less than a high school education was 10.3%. The rate for high school graduation (which includes equivalency) was 28.5%, some collage 39.6% and Bachelor’s degree or higher was 21.6%. Of the women with at least a Bachelor’s degree or higher, 23.3% had a graduate or professional degree in Utah compared to 33.8% nationally. Educational attainment in the U.S. was 15.6% for less than high school, 30.2% for high school graduation, 29.9% for some college and 24.3% for a Bachelor’s degree or higher.[1] Utah appears to have a much larger proportion of females with some college but the rates drop when compared to the U.S. in obtaining a least a Bachelor’s degree or higher.


Utah’s average household size was 3.1 people, compared to 2.6 in the U.S. Families made up 75% of the households in Utah. This figure includes both married-couple families (62%) and other families (13%). Nonfamily households made up 25% of all households in Utah, comprised mostly of people living alone. Female householders with no husband present made up 69% of the ‘other family’ category which included non-married households. In the U.S., families made up 67% of the households which included both married-couple families (50%) and other families (17%). Other families with a female householder made up a larger proportion for the U.S. at 73%.[1]

Marriage and Divorce

Marriage and divorce rates are the number of marriages or divorces per 1,000 persons in the population. The marriage rate was 9.6 compared to 7.4 for the U.S. There were 58.5% of females 15 years and over that were married in Utah compared to 51.0% in the U.S. Slightly fewer single females, never married, were found in Utah (24.5% vs. 25.5%). Utah also had fewer divorced females than the U.S., 10.0% in Utah compared to 11.5% nationally. Utah’s 2004 divorce rate was similar to that found in the U.S. (4.0 vs. 3.7).[2]


The median annual household income in the past 12 months (inflation adjusted dollars) for Utah in 2005 was $47,934 compared to $46,242 in the U.S. Utah’s median household income has generally kept pace with that in the U.S. because Utah’s households are larger and the per capita income in Utah is lower than the U.S. ($20,814 vs. $25,035). For females over the age of 14 working within the past year the median income was lower for Utahns ($14,969 vs. $18,651).[1]


Poverty takes into account both income and family size, and has both immediate and long-lasting effects on health. Income provides an assessment of the financial resources available to individual persons or families for basic necessities (e.g., food, clothing, and health care) to maintain or improve their well-being. Ten percent of Utahns were living in poverty. Eight percent of all families and 25% of families with a female head of household with no husband present had incomes below the poverty level. Females living at or below the federal poverty level in Utah were highest among the 18-34 year age group at 43.0%. Females under 18 years of age comprised 28.3% of females living below poverty while there were 22.0% of the 35-64 year old age group living in poverty and the lowest rate was among 65+ year old females (6.7%). The U.S. rates for females living in poverty by age group were not the same as Utahns. There were 30.5% under age 18, 30.1% age 18-34, 28.5% age 35-64 and 11.0% over age 64.[1]


  1. U.S. Census Bureau, 2005 American Community Survey accessed 1/11/07 from
  2. Marriage and Divorce, Population Characteristics (Education, Income and Poverty) Retrieved on 1/11/07 from Utah Department of Health, Center for Health Data, Indicator-Based Information System for Public Health website:

Stroke in Women


Every year stroke strikes approximately 750,000 Americans killing 160,000. This year over 100,000 U.S. women under age 65 will have a stroke.[1] Stroke is the third leading cause of death in the United States and in Utah and twice as many women will die this year from a stroke than from breast cancer.

A stroke is an attack on the brain. This can occur in two ways, the first is when a blood clot blocks an artery (a blood vessel that carries blood from the heart to the body), this is called an ischemic stroke and occurs in about 83% of cases. Ischemic strokes can be caused by the build up of fatty deposits that line the vessel walls. The second kind of stoke is called a hemorrhagic stroke, a bleed, and occurs when a weakened blood vessel breaks, causing an interruption in blood flow to the brain. Hemorrhagic strokes happen in about 17% of stroke cases.[2] Increased time from stroke symptom onset to treatment is associated with increased morbidity and death. Unfortunately, studies show that women are more likely to delay seeking treatment for stroke than are men and therefore, have a higher risk for death and disability.

The HP 2010 goal for stroke is: Reduce stroke deaths to 48 per 100,000 population.[3]

Risk Factors

There are many risk factors for stroke; some that you can change and some that you can not. While Utah is a healthier state than many others, there is room for improvement. Of Utah women, 18 years of age and older, in 2005:[4]

  1. 20.2% had High Blood Pressure (greater than or equal to 120/80).
  2. 29.5% had High Blood Cholesterol (a total blood cholesterol level of 240mg/dL or higher)
  3. 9.3% Smoked
  4. 5.8% had Diabetes.
  5. 46.1% were Physically Inactive (did not get enough exercise, a total of 30 minutes a day most days of the week).
  6. 47.4% were Overweight or Obese (BMI greater than or equal to 25).

Higher Risks for Women

Women under the age of 55 have other risk factors that include; migraine, birth control pills, hormone replacement therapy, and clotting disorders. Women who are on any of these therapies or suffer from either condition should be aware that they can increase the likelihood of having a stroke and that controlling other risk factors can decrease the chance of having a stroke. Risk factors are cumulative, reducing even one risk can greatly lower your chances of having a stroke.[5]

Utah Women and Stroke

The age-adjusted percentage of adults age 18 and older who reported ever having a stroke was similar between males and females between 2001 and 2005 (2.0% for males and 2.1% for females). However, during this same time period, Utah women had a higher age-adjusted stroke mortality rate (54.4/100,000) when compared to men (46.4/100,000). In Utah, between 2001 and 2005, 60.7% of stroke deaths were in women.[6]

Figure 1. Stroke mortality by year and gender, Utah and U.S. 1996-2005. (Utah Death Certificate Database, Office of Vital Records, Utah Department of Health)

Although in 2005, the age-adjusted hospitalization rates were higher for Utah males (16.4 per 10,000) than females (14.6 per 10,000), the actual number of women hospitalized for stroke in Utah exceeded that for men, 1490 versus 1380, respectively.[7]

Common warning sighs of stroke:

• Sudden numbness or weakness in the face, arms, or leg-especially if it is on one side of the body only
• Sudden vision loss or blurriness in one or both eyes
• Sudden loss of balance, dizziness, or coordination
• Sudden trouble walking
• Sudden confusion or trouble with your speech.


Eighty percent of all strokes are preventable.9 Knowing your risk factors and controlling those that you can will help to prevent you from having a stroke. Maintain a healthy blood pressure, cholesterol, weight, and be physically active. If you smoke–quit. To learn more about stroke, warning signs, and recovery you can visit:

  • National Stroke Association:
  • American Stroke Association:
  • Utah Heart Highway:


  1. American Stroke Association. What are the Types of Stroke? from Accessed March 13, 2007.
  2. Utah Dept of Health. Stroke: What is a Stroke? from Accessed December 28, 2006.
  3. U.S. Department of Health and Human Services. Healthy People 2010 (Conference Edition, in Two Volumes). Washington, D.C: January 2000.
  4. Utah Behavioral Risk Factor Surveillance System, Office of Public Health Assessment, Utah Department of Health, 2005.
  5. American Stroke Association. Hidden Risk Factors for Women. from identifier=3030391. Accessed March 14, 2007.
  6. Utah Department of Health, Heart Disease and Stroke Prevention Program. The Impact of Heart Disease and Stroke in Utah, 2007. SLC: March 2007.
  7. Utah Department of Health, Heart Disease and Stroke Prevention Program. The Impact of Heart Disease and Stroke in Utah, 2007. SLC: March 2007.
  8. Utah Dept of Health. Stroke: Risk Factors. from Accessed December 28, 2006.
  9. National Stroke Association. Public Stroke Prevention Guidelines. from Accessed March 13, 2007.